Systems of logico-probabilistic (LP) reasoning characterize inference from conditional assertions interpreted as expressing high conditional probabilities. In the present article, we investigate four prominent LP systems (namely, systems O, P, Z, and QC) by means of computer simulations. The results reported here extend our previous work in this area, and evaluate the four systems in terms of the expected utility of the dispositions to act that derive from the conclusions that the systems license. In addition to conforming to the (...) dominant paradigm for assessing the rationality of actions and decisions, our present evaluation complements our previous work, since our previous evaluation may have been too severe in its assessment of inferences to false and uninformative conclusions. In the end, our new results provide additional support for the conclusion that (of the four systems considered) inference by system Z offers the best balance of error avoidance and inferential power. Our new results also suggest that improved performance could be achieved by a modest strengthening of system Z. (shrink)

Conceptual combination performs a fundamental role in creating the broad range of compound phrases utilised in everyday language. This article provides a novel probabilistic framework for assessing whether the semantics of conceptual combinations are compositional, and so can be considered as a function of the semantics of the constituent concepts, or not. While the systematicity and productivity of language provide a strong argument in favor of assuming compositionality, this very assumption is still regularly questioned in both cognitive science and (...) philosophy. Additionally, the principle of semantic compositionality is underspecifi ed, which means that notions of both "strong" and "weak" compositionality appear in the literature. Rather than adjudicating between different grades of compositionality, the framework presented here contributes formal methods for determining a clear dividing line between compositional and non-compositional semantics. In addition, we suggest that the distinction between these is contextually sensitive. Compositionality is equated with a joint probability distribution modeling how the constituent concepts in the combination are interpreted. Marginal selectivity is introduced as a pivotal probabilistic constraint for the application of the Bell/CH and CHSH systems of inequalities. Non-compositionality is equated with a failure of marginal selectivity, or violation of either system of inequalities in the presence of marginal selectivity. This means that the conceptual combination cannot be modeled in a joint probability distribution, the variables of which correspond to how the constituent concepts are being interpreted. The formal analysis methods are demonstrated by applying them to an empirical illustration of twenty-four non-lexicalised conceptual combinations. (shrink)

In previous work, we studied four well known systems of qualitative probabilistic inference, and presented data from computer simulations in an attempt to illustrate the performance of the systems. These simulations evaluated the four systems in terms of their tendency to license inference to accurate and informative conclusions, given incomplete information about a randomly selected probability distribution. In our earlier work, the procedure used in generating the unknown probability distribution (representing the true stochastic state of the world) tended to (...) yield probability distributions with moderately high entropy levels. In the present article, we present data charting the performance of the four systems when reasoning in environments of various entropy levels. The results illustrate variations in the performance of the respective reasoning systems that derive from the entropy of the environment, and allow for a more inclusive assessment of the reliability and robustness of the four systems. (shrink)

We consider two ways one might use algorithmic randomness to characterize a probabilistic law. The first is a generative chance* law. Such laws involve a nonstandard notion of chance. The second is a probabilistic* constraining law. Such laws impose relative frequency and randomness constraints that every physically possible world must satisfy. While each notion has virtues, we argue that the latter has advantages over the former. It supports a unified governing account of non-Humean laws and provides independently motivated (...) solutions to issues in the Humean best-system account. On both notions, we have a much tighter connection between probabilistic laws and their corresponding sets of possible worlds. Certain histories permitted by traditional probabilistic laws are ruled out as physically impossible. As a result, such laws avoid one variety of empirical underdetermination, but the approach reveals other varieties of underdetermination that are typically overlooked. (shrink)

Is it right to convict a person of a crime on the basis of purely statistical evidence? Many who have considered this question agree that it is not, posing a direct challenge to legal probabilism – the claim that the criminal standard of proof should be understood in terms of a high probability threshold. Some defenders of legal probabilism have, however, held their ground: Schoeman (1987) argues that there are no clear epistemic or moral problems with convictions based on purely (...) statistical evidence, and speculates that our aversion to such convictions may be nothing more than an irrational bias. More recently, Hedden and Colyvan (2019, section VI) describe our reluctance to convict on the basis of purely statistical evidence as an ‘intuition’, but suggest that there may be no ‘in principle’ problem with such convictions (see also Papineau, forthcoming, section 6). In this paper, I argue that there is, in some cases, an in principle problem with a conviction based upon statistical evidence alone – namely, it commits us to a precedent which, if consistently followed through, could lead to the deliberate conviction of an innocent person. I conclude with some reflections on the idea that the criminal justice system should strive to maximise the accuracy of its verdicts – and the related idea that we should each strive to maximise the accuracy of our beliefs. (shrink)

It has recently been remarked that the argument for physicalism from the causal closure of the physical is incomplete. It is only effective against mental causation manifested in the action of putative mental forces that lead to acceleration of particles in the nervous system. Based on consideration of anomalous, physically unaccounted-for correlations of neural events, I argue that irreducible mental causation whose nature is at least prima facie probabilistic is conceivable. The manifestation of such causation should be accompanied (...) by a local violation of the Second Law of thermodynamics. I claim that mental causation can be viewed as the disposition of mental states to alter the state probability distribution within the nervous system, with no violation of the conservation laws. If confirmed by neurophysical research, it would indicate a kind of causal homogeneity of the world. Causation would manifest probabilistically in both quantum mechanical and psychophysical systems, and the dynamics of both would be determined by the temporal evolution of the corresponding system state function. Finally, I contend that a probabilistic account of mental causation can consistently explain the character of selectional states that ensure the uniformity of causal patterns, as well as the fact that different physical realizers of a mental property cause the same physical effects in different contexts. (shrink)

There are numerous formal systems that allow inference of new conditionals based on a conditional knowledge base. Many of these systems have been analysed theoretically and some have been tested against human reasoning in psychological studies, but experiments evaluating the performance of such systems are rare. In this article, we extend the experiments in [19] in order to evaluate the inferential properties of c-representations in comparison to the well-known Systems P and Z. Since it is known that System Z (...) and c-representations mainly differ in the sorts of inheritance inferences they allow, we discuss subclass inheritance and present experimental data for this type of inference in particular. (shrink)

The principle of the common cause claims that if an improbable coincidence has occurred, there must exist a common cause. This is generally taken to mean that positive correlations between non-causally related events should disappear when conditioning on the action of some underlying common cause. The extended interpretation of the principle, by contrast, urges that common causes should be called for in order to explain positive deviations between the estimated correlation of two events and the expected value of their correlation. (...) The aim of this paper is to provide the extended reading of the principle with a general probabilistic model, capturing the simultaneous action of a system of multiple common causes. To this end, two distinct models are elaborated, and the necessary and sufficient conditions for their existence are determined. (shrink)

This work describes an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework.

Many tasks in statistical and causal inference can be construed as problems of entailment in a suitable formal language. We ask whether those problems are more difficult, from a computational perspective, for causal probabilistic languages than for pure probabilistic (or “associational”) languages. Despite several senses in which causal reasoning is indeed more complex—both expressively and inferentially—we show that causal entailment (or satisfiability) problems can be systematically and robustly reduced to purely probabilistic problems. Thus there is no jump (...) in computational complexity. Along the way we answer several open problems concerning the complexity of well-known probability logics, in particular demonstrating the ${\exists \mathbb {R}}$ -completeness of a polynomial probability calculus, as well as a seemingly much simpler system, the logic of comparative conditional probability. (shrink)

Entanglement is one of the most striking features of quantum mechanics, and yet it is not specifically quantum. More specific to quantum mechanics is the connection between entanglement and thermodynamics, which leads to an identification between entropies and measures of pure state entanglement. Here we search for the roots of this connection, investigating the relation between entanglement and thermodynamics in the framework of general probabilistic theories. We first address the question whether an entangled state can be transformed into another (...) by means of local operations and classical communication. Under two operational requirements, we prove a general version of the Lo-Popescu theorem, which lies at the foundations of the theory of pure-state entanglement. We then consider a resource theory of purity where free operations are random reversible transformations, modelling the scenario where an agent has limited control over the dynamics of a closed system. Our key result is a duality between the resource theory of entanglement and the resource theory of purity, valid for every physical theory where all processes arise from pure states and reversible interactions at the fundamental level. As an application of the main result, we establish a one-to-one correspondence between entropies and measures of pure bipartite entanglement and exploit it to define entanglement measures in the general probabilistic framework. In addition, we show a duality between the task of information erasure and the task of entanglement generation, whereby the existence of entropy sinks (systems that can absorb arbitrary amounts of information) becomes equivalent to the existence of entanglement sources (correlated systems from which arbitrary amounts of entanglement can be extracted). (shrink)

Pierre-Sylvain Régis’s Cartesianism is quite singular in seventeenth-century French philosophy. Though, can we speak of a form of experimental science in Régis’s work? After exploring his notions of ‘system’ and ‘hypothesis’, I will define his position in relation to Claude Perrault, Jacques Rohault, and the Royal Society. I argue, first, that the contrasts which traverse French science are not so much about the use of experiments but about whether or not observational data can be traced back to hypotheses and (...) to a coherent system. Secondly, that we can detect a significant similarity between Boyle’s positions and the views expressed by Perrault and also by Régis. Lastly, that French science, even in its Cartesian version, is much more probabilistic than English experimental philosophy. (shrink)

In the following we will investigate whether von Mises’ frequency interpretation of probability can be modified to make it philosophically acceptable. We will reject certain elements of von Mises’ theory, but retain others. In the interpretation we propose we do not use von Mises’ often criticized ‘infinite collectives’ but we retain two essential claims of his interpretation, stating that probability can only be defined for events that can be repeated in similar conditions, and that exhibit frequency stabilization. The central idea (...) of the present article is that the mentioned ‘conditions’ should be well-defined and ‘partitioned’. More precisely, we will divide probabilistic systems into object, initializing, and probing subsystem, and show that such partitioning allows to solve problems. Moreover we will argue that a key idea of the Copenhagen interpretation of quantum mechanics (the determinant role of the observing system) can be seen as deriving from an analytic definition of probability as frequency. Thus a secondary aim of the article is to illustrate the virtues of analytic definition of concepts, consisting of making explicit what is implicit. (shrink)

Abstract -/- This paper establishes the mathematical foundation of CODES (Chirality of Dynamic Emergent Systems), introducing a unifying framework for structured emergence across disciplines. We formalize prime-driven resonance equations, a novel class of nonlinear phase-locking dynamics, and a generalized coherence metric to quantify system stability across physical, biological, and cognitive domains. -/- By extending harmonic analysis, prime number theory, and topological invariants, we propose a universal resonance function that governs the transition from stochastic disorder to structured order. This framework: (...) • Resolves fundamental paradoxes in probability theory by demonstrating that randomness is a projection of underlying resonance structures. • Redefines symmetry-breaking as a phase-locked emergence process, replacing traditional group-theoretic formulations. • Introduces a computable coherence model that predicts emergent stability across complex adaptive systems. -/- Finally, we explore implications for cosmology, AI, and quantum gravity, demonstrating that mathematical reality is fundamentally a structured resonance field, not a probabilistic space. (shrink)

We drive our lives permanently by decisions YES/NO, and even we no longer distinguish the elementary intermediary steps of such decisions most often, they form stereotyped chains that once triggered, they run unconsciously, daily facilitating our activities. We lead our lives actually by conscious decisions, each of such decisions establishing our future trajectory. The YES/NO dipole is actually the elemental evaluation and decisional unit in the informational transmission/reception equipment and lines and in computers, respectively. Based on a binary probabilistic (...) system, this is defined as a unit of information (Bit). We operate therefore as an informational system and we actually live in a bipolar universe, which is fundamentally informational. Indeed, the laws of nature and its equilibrium or steady state conditions are based on bipolar units with opposite characteristics, such as action/reaction, attraction/rejection, gravity/anti-gravity, matter/antimatter, entropy/anti-entropy, to enumerate just a few examples. As part of this bipolar universe, we are also bipolar entities connected to information and matter. Starting from the informational features of the human being, seven informational components are identified, forming the informational system of the human body, distinguished by their different functions, reflected at the conscious level through the center Iknow (the memory, including whole life experience), Iwant (decisions center), Iove (emotions), Iam (body status), Icreate (informational genetic transmitter), Icreated (genetic generator inherited from parents) and Ibelieve, which is the gateway to the antientropic component, favorable to maintain the life structure and functioning. Taking into account the characteristics of these centers, it is discussed the life cycle and are deduced suitable conclusions concerning an optimal, active lifestyle, that would contribute to a successful life, aging and destiny. (shrink)

The Comprehensive Human Decision-Making Equation presents a robust model for understanding Holistic Free Will (HFW), conceptualizing decision-making as an autonomous, non-deterministic process within a complex network of influences. This model addresses the Infinite Regress issue by portraying free will as an emergent property of interacting layers, including internal beliefs, external contexts, emotional responses, cognitive biases, and habitual tendencies. Departing from traditional linear models, the equation adopts a systemic framework where each choice reflects a cumulative utility, integrating multiple components such as (...) personal, ethical, social, and temporal utilities. This holistic approach emphasizes the probabilistic nature of free will, challenging deterministic interpretations and highlighting the ethical and relational dimensions of autonomy. By situating free will within a structured yet adaptive process, the model supports the notion that true autonomy is ethically aligned, relational, and embedded in a flexible reality, thereby promoting communal and ethical development. (shrink)

The main thesis of this paper is directed against the traditional (cognitivetheoretical) definition of the concept which claims that the concept is the '' thought about the essence of the object being thought'', i.e. that it is “a set of essential features or essential characteristics of an object''. But the '' set of essential features or essential characteristics of an object of thought'' is a '' content’’ of the thought. The thought about the essence of an object is definition and (...) the concept is not definition but the part of definition! Besides as the part of formal structure of thought, the concept possesses calculative logical properties that in formal logic (be it syllogistics, or the logic of propositions, or the logic of predicates) come to the front place of formal logical computation. Without the calculative properties of the concept, there would be no calculative properties of propositions which express the thought (thought structures). The calculative properties of a concept include the (1) degree of its logical generality (degree of variability), the (2) logical relations it can establish within the whole of the conceptual content, the (3) operability of the concept in structure of affirmation and negation, the (4) deducibility of either axiomatic or probabilistic systems. Therefore, I believe that, from the logical point of view, the definition of a concept should be applied in favor of its calculative properties that it possesses. (shrink)

Purpose: This article aims to highlight key indicators of residents' quality of life in a specific contemporary building in Kruja, Albania. -/- Design/Method/Approach: A questionnaire with 30 questions was prepared for the inhabitance, and the Binary or Tobit probabilistic models were taken into consideration as part of the methodology, to conclude. The study will further analyze the implications of the inhabitants and their behavior in a specific contemporary building in the city of Kruja. It was examined the statistical significance (...) of each variable (questions) in the models elaborated with EViews 8 software. The stable models that are associated with the “Log-likelihood” statistics were statistically significant at a significance level of p < 5%, or with 95% confidence, based on the model tests. -/- Findings: The study concluded that the most statistically significant quality of life indicators part of the questionnaire is related to the typology of the apartments, methods of cooling during summer, present living conditions, apartment improvement, apartment orientation, and time spent in the living room. Furthermore, the study reveals that most of the quality-of-life indicators (part of the questionnaire) are not statistically important, so they will not be considered part of the models created in the article. The study reveals that increasing the living space and improving orientation is crucial to enhance the satisfaction of apartment inhabitants. When apartment sizes increase and orientation is improved, residents are more likely to opt for fans over air conditioners to reduce electricity costs and avoid installing additional cooling facilities during summer. They believe that better living conditions require larger apartments, additional water supply, increased electrical costs, and more time spent in the living room. The inhabitants also emphasize the importance of reducing moisture levels, decreasing window opening frequency, and increasing time spent with family. Interestingly, a one-degree improvement in summer cooling methods (e.g., switching from air blowers to air conditioning) corresponds to a one-degree improvement in winter heating methods (e.g., switching from gas to electricity), leading to a heightened need for clean electric heating. Overall, the study emphasizes the importance of meeting the physical and spatial needs of the residents to enhance their overall satisfaction and quality of life. Urban policies significantly impact housing affordability, quality, transport systems, environmental sustainability, and social equity, affecting overall living standards and economic growth. Cities must create well-designed policies that consider residents' needs and study findings to ensure sustainable development and citizen welfare. -/- Theoretical Implications: Gujarati’s (Basic Economics) theory was developed in the article. -/- Practical Implications: This study will serve as an indicator to analyze the further improvements that might occur in the specific building (not just in the city of Kruja), considering the main quality of life indicators. -/- Originality/Value: The article will serve as a base for further analysis of resident’s behavior and their social impact in the community in order to be aware of their needs for further developments in the construction field. -/- Research Limitations/Future Research: The findings depend profoundly on the type of building the residents are living in. The research stream that can be inspired by the research is strongly related to mathematical regression models, statistics, and probability. -/- Paper Type: Empirical . (shrink)

The development of machine learning and deep learning (DL) in the field of AI (artificial intelligence) is the direct result of the advancement of nano-electronics. Machine learning is a function that provides the system with the capacity to learn from data without being programmed explicitly. It is basically a mathematical and probabilistic model. DL is part of machine learning methods based on artificial neural networks, simply called neural networks (NNs), as they are inspired by the biological NNs that (...) constitute organic brains. Despite its similarity to biological organs such as human brains, major problems arise in trying to attribute moral responsibility to autonomic systems based on hardware including nano-electronic devices, which are sought to replace humans (moral agents) in the context of AI. It is suggested that the required emotional environment which enables actions according to reasons in humans is not witnessed at AI devices. Though AI technology raises an enticing resemblance to human actions, this resemblance is to be considered with a skeptical eye. It is because actions are associated with reasons while causes are connected to operations. Human agents are capable of acting upon their reasons, while AI devices are limited only to operations as they are conditioned by their programming, which is considered as an embodiment of some causes. As moral responsibility goes hand in hand with the capacity to act (according to reasons), attributing moral responsibility to AI devices is revealed to be but a misleading metaphor. (shrink)

The demands of fair machine learning are often expressed in probabilistic terms. Yet, most of the systems of concern are deterministic in the sense that whether a given subject will receive a given score on the basis of their traits is, for all intents and purposes, either zero or one. What, then, can justify this probabilistic talk? We argue that the statistical reference classes used in fairness measures can be understood as defining the probability that hypothetical persons, who (...) are representative of social roles, will receive certain goods. We call these hypothetical persons “representative individuals.” We claim that what we owe to actual, concrete individuals—whose individual chances of receiving the good in the system might be extreme (i.e., either zero or one)—is that their representative individual has an appropriate probability of receiving the good in question. While less immediately intuitive than other approaches, we argue that the representative individual approach has important advantages over other ways of making sense of this probabilistic talk in the context of fair machine learning. (shrink)

This paper develops a trivalent semantics for the truth conditions and the probability of the natural language indicative conditional. Our framework rests on trivalent truth conditions first proposed by Cooper (1968) and Belnap (1973) and it yields two logics of conditional reasoning: (i) a logic C of certainty-preserving inference; and (ii) a logic U for uncertain reasoning that preserves the probability of the premises. We show systematic correspondences between trivalent and probabilistic representations of inferences in either framework, and we (...) use the distinction between the two systems to cast light on the validity of inferences such as Modus Ponens, Or-To-If, and Conditional Excluded Middle. Specifically, the conditional behaves monotonically in C, but non-monotonically in U; Modus Ponens is valid in C, but valid in U only for non-nested conditionals. The result is a unified account of the semantics and epistemology of indicative conditionals that can be fruitfully applied to analyzing the validity of conditional inferences. (shrink)

The Ramsey Test is considered to be the default test for the acceptability of indicative conditionals. I will argue that it is incompatible with some of the recent developments in conceptualizing conditionals, namely the growing empirical evidence for the _Relevance Hypothesis_. According to the hypothesis, one of the necessary conditions of acceptability for an indicative conditional is its antecedent being positively probabilistically relevant for the consequent. The source of the idea is _Evidential Support Theory_ presented in Douven (2008). I will (...) defend the hypothesis against alleged counterexamples, and show that it is supported by growing empirical evidence. Finally, I will present a version of the Ramsey test which incorporates the relevance condition and therefore is consistent with growing empirical evidence for the relevance hypothesis. (shrink)

LLMs have dramatically improved in capabilities in recent years. This raises the question of whether LLMs could become genuine agents with beliefs and desires. This paper demonstrates an in principle limit to LLM agency, based on their architecture. LLMs are next word predictors: given a string of text, they calculate the probability that various words can come next. LLMs produce outputs that reflect these probabilities. I show that next word predictors are exploitable. If LLMs are prompted to make probabilistic (...) predictions about the world, these predictions are guaranteed to be incoherent, and so Dutch bookable. If LLMs are prompted to make choices over actions, their preferences are guaranteed to be intransitive, and so money pumpable. In short, the problem is that selecting an action based on its potential value is structurally different then selecting the description of an action that is most likely given a prompt: probability cannot be forced into the shape of expected value. The in principle exploitability of LLMs raises doubts about how agential they can become. This exploitability also offers an opportunity for humanity to safely control such AI systems. (shrink)

This chapter will review selected aspects of the terrain of discussions about probabilities in statistical mechanics (with no pretensions to exhaustiveness, though the major issues will be touched upon), and will argue for a number of claims. None of the claims to be defended is entirely original, but all deserve emphasis. The first, and least controversial, is that probabilistic notions are needed to make sense of statistical mechanics. The reason for this is the same reason that convinced Maxwell, Gibbs, (...) and Boltzmann that probabilities would be needed, namely, that the second law of thermodynamics, which in its original formulation says that certain processes are impossible, must, on the kinetic theory, be replaced by a weaker formulation according to which what the original version deems impossible is merely improbable. Second is that we ought not take the standard measures invoked in equilibrium statistical mechanics as giving, in any sense, the correct probabilities about microstates of the system. We can settle for a much weaker claim: that the probabilities for outcomes of experiments yielded by the standard distributions are effectively the same as those yielded by any distribution that we should take as a representing probabilities over microstates. Lastly, (and most controversially): in asking about the status of probabilities in statistical mechanics, the familiar dichotomy between epistemic probabilities (credences, or degrees of belief) and ontic (physical) probabilities is insufficient; the concept of probability that is best suited to the needs of statistical mechanics is one that combines epistemic and physical considerations. (shrink)

We reconsider the pragmatic interpretation of intuitionistic logic [21] regarded as a logic of assertions and their justi cations and its relations with classical logic. We recall an extension of this approach to a logic dealing with assertions and obligations, related by a notion of causal implication [14, 45]. We focus on the extension to co-intuitionistic logic, seen as a logic of hypotheses [8, 9, 13] and on polarized bi-intuitionistic logic as a logic of assertions and conjectures: looking at the (...) S4 modal translation, we give a de nition of a system AHL of bi-intuitionistic logic that correctly represents the duality between intuitionistic and co-intuitionistic logic, correcting a mistake in previous work [7, 10]. A computational interpretation of cointuitionism as a distributed calculus of coroutines is then used to give an operational interpretation of subtraction.Work on linear co-intuitionism is then recalled, a linear calculus of co-intuitionistic coroutines is de ned and a probabilistic interpretation of linear co-intuitionism is given as in [9]. Also we remark that by extending the language of intuitionistic logic we can express the notion of expectation, an assertion that in all situations the truth of p is possible and that in a logic of expectations the law of double negation holds. Similarly, extending co-intuitionistic logic, we can express the notion of conjecture that p, de ned as a hypothesis that in some situation the truth of p is epistemically necessary. (shrink)

One finds, in Maxwell's writings on thermodynamics and statistical physics, a conception of the nature of these subjects that differs in interesting ways from the way that they are usually conceived. In particular, though—in agreement with the currently accepted view—Maxwell maintains that the second law of thermodynamics, as originally conceived, cannot be strictly true, the replacement he proposes is different from the version accepted by most physicists today. The modification of the second law accepted by most physicists is a (...) class='Hi'>probabilistic one: although statistical fluctuations will result in occasional spontaneous differences in temperature or pressure, there is no way to predictably and reliably harness these to produce large violations of the original version of the second law. Maxwell advocates a version of the second law that is strictly weaker; the validity of even this probabilistic version is of limited scope, limited to situations in which we are dealing with large numbers of molecules en masse and have no ability to manipulate individual molecules. Connected with this is his concept of the thermodynamic concepts of heat, work, and entropy; on the Maxwellian view, these are concepts that must be relativized to the means we have available for gathering information about and manipulating physical systems. The Maxwellian view is one that deserves serious consideration in discussions of the foundation of statistical mechanics. It has relevance for the project of recovering thermodynamics from statistical mechanics because, in such a project, it matters which version of the second law we are trying to recover. (shrink)

This is a sketch of the basis and role of consciousness and the minimally required elements and constraints of any setting that may produce consciousness. It proposes that consciousness (as we know it) is a biologically-mediated product of evolved recursive and hierarchically nested representational systems that obey information theoretic principles and Bayesian (probabilistic) feedback and feedforward predictive modeling processes.

In quantum mechanics, the term “creativity” is amplified, since natural events form the constant transition from possibility to reality, according to the ontological probabilism of the Schrödinger equation. The completion of the quantum theory through the concept of the Grand Unified Theories, and especially through the yet incomplete superstring theory, reveals that at the micro level of creation of sub-atomic particles or space, motion literally comes prior to Being and objects are forms of a motion which suggests a constant transition (...) from possibility to reality. In non – linear physics of complex systems, the term “creativity” does not simply correspond to the initial emergence of the universe (big bang) or to the sub-atomic scale processes described by quantum mechanics, the Grand Unified Theories and the superstring theory, but is expanded to all aspects of nature: i.e. physical - chemical, ecological, psychological – mental aspect. So, through the non – linear physics theory, macroscopically viewed beings are constructed, holistic forms of motion, in order for the whole to gain a non reducible (therefore the whole is constantly being produced) ontological meaning which characterizes the operation of the part. Combining the theories of quantum mechanics and relativity, it could be stated that modern physics abolishes the customary perception concerning the natural phenomena, which were concerned as a constant transformation of a fundamental substance. On the contrary, the contemporary description of the natural world by physics and mathematics corresponds to Morphodynamics, i.e. the description of the world as creation of all cosmic shapes from a zero point, on all cosmic levels. From this point of view, zero is understood as the absence of shape, while the notion of an unshaped eternal substance is weakened and does not seem to be able to be justified by the evolution of scientific thought. The “beings” and their “substance” are assimilated to forms of movement that have already been created or that are being created, and constitute motion inside motion. (shrink)

I present three reasons why philosophers of science should be more concerned about violations of causal faithfulness (CF). In complex evolved systems, mechanisms for maintaining various equilibrium states are highly likely to violate CF. Even when such systems do not precisely violate CF, they may nevertheless generate precisely the same problems for inferring causal structure from probabilistic relationships in data as do genuine CF-violations. Thus, potential CF-violations are particularly germane to experimental science when we rely on probabilistic information (...) to uncover the DAG, rather than already knowing the DAG from which we could predict the right experiments to ‘catch out’ the hidden causal relationships. (shrink)

-/- The Integration of Angelito Malicse’s Universal Formula with Quantum Computer Design, AGI Algorithmic Design, and Education -/- In the pursuit of developing intelligent systems, the realms of quantum computing, artificial general intelligence (AGI), and educational frameworks face the significant challenge of balancing complex feedback mechanisms, ethical decision-making, and system stability. The universal formula developed by Angelito Malicse provides a pioneering approach to understanding free will, human behavior, and decision-making. His three laws, deeply rooted in the concept of natural (...) balance, offer valuable insights into addressing problems related to technological systems, such as quantum computers and AGI. This essay explores how Malicse’s universal formula can be integrated into quantum computer design, AGI algorithmic development, and educational models, emphasizing the importance of feedback loops, balance, and ethical decision-making as critical components in these fields. -/- The Universal Formula: An Overview -/- Angelito Malicse’s universal formula consists of three key laws: -/- 1. The Law of Karma (Cause and Effect): This law posits that every action leads to a consequence. It emphasizes that systems—whether natural or man-made—must function without defects to ensure they operate effectively and safely. Any imbalance or disruption in the system causes dysfunction, whether the system is biological, mechanical, or computational. -/- 2. The Homeostasis Principle: This principle asserts that systems—be they biological, technological, or social—must maintain equilibrium to function correctly. When an imbalance occurs, the system seeks to restore balance. This is a critical process in all functional systems, from the human body to technological networks. -/- 3. The Ethical Decision-Making Law: This law underscores the importance of ethical decision-making within systems. It suggests that choices must promote balance and avoid disrupting the natural harmony of the system. If decisions violate this balance, they result in negative consequences, reflecting the idea that imbalance leads to dysfunction in both societal and technological systems. -/- These principles, while addressing human behavior and societal functioning, also have profound implications for the development of quantum computing and AGI, areas that are critical to future advancements in technology. -/- Quantum Computing and the Universal Formula -/- Quantum computing represents a revolutionary leap in computational power, utilizing quantum mechanics principles—such as superposition, entanglement, and interference—to solve problems in parallel. Quantum systems, however, are highly sensitive to errors and disturbances, which could affect their ability to function reliably. Thus, understanding and applying the universal formula to quantum computer design is essential. -/- Quantum Causal Inference and the Law of Karma -/- Quantum computing is built on probabilistic models where each quantum state evolves based on prior interactions, an approach that mirrors the concept of cause and effect. Quantum systems follow causal inference, meaning that each quantum operation is influenced by the previous one. This aligns directly with the Law of Karma—every operation in a quantum computer has consequences, which can either lead to a stable state or introduce error. If the system is defective or disrupted, it results in instability, just as a defective system in nature or society fails to function correctly. -/- Quantum algorithms, such as those used in quantum machine learning, rely heavily on cause-effect relationships to guide the computation. The delicate balance between quantum states and operations mirrors the need for balance in natural systems: if a quantum system is not free from errors, its performance will degrade, reflecting Malicse’s principle that systems must be free of defects to operate properly. -/- Quantum Neural Networks (QNNs) and Feedback Mechanisms -/- Quantum Neural Networks (QNNs) aim to replicate the neural network structure of the human brain using quantum bits (qubits) and quantum gates. These networks utilize feedback loops, where the system continuously adapts and updates based on prior outputs, enhancing its learning process. This closely aligns with Malicse’s feedback loop principle, which emphasizes the importance of continuous adjustment based on environmental feedback. -/- QNNs utilize quantum feedback to optimize learning. However, just like biological systems, they require feedback that operates in balance, ensuring that each decision made by the system aligns with previous learnings and the larger goal of the system. For a quantum system to achieve reliable performance, the feedback mechanism must be balanced and precise, aligning with Malicse’s view that all systems—whether biological or technological—must act to restore balance when disrupted. -/- Homeostasis in Quantum Systems -/- The ability of quantum systems to maintain homeostasis—to return to a balanced state after a disturbance—is another vital aspect of quantum computing. Quantum error correction algorithms play a central role in ensuring that quantum states do not deviate significantly from their intended positions due to noise or errors. These mechanisms allow quantum systems to maintain internal equilibrium despite external interference, mirroring the concept of homeostasis in biological systems. -/- Malicse’s Homeostasis Principle is directly applicable here: just as biological systems restore balance to ensure survival, quantum systems require constant error-correction and recalibration to maintain balance. This principle ensures that quantum computations are accurate and that imbalances (such as errors or instabilities) are corrected swiftly, maintaining the overall stability of the quantum system. -/- AGI and the Universal Formula -/- The field of AGI seeks to develop machines capable of generalizing knowledge and solving complex problems across multiple domains. As AGI systems evolve, the challenge lies in ensuring they adhere to ethical principles and maintain balance within their decision-making processes. The universal formula offers guidance on how AGI can be structured to make decisions that reflect the principles of natural balance. -/- Feedback Mechanisms and Ethical Decision-Making -/- One of the core challenges of AGI is ensuring that it can make decisions ethically, even when faced with complex, ambiguous situations. AGI systems learn from feedback, adapting their decisions based on both the data they receive and the ethics embedded within their algorithms. The feedback loop in AGI is similar to that of human decision-making—data inputs (environmental feedback) are processed, and decisions are refined to optimize outcomes. -/- Malicse’s Ethical Decision-Making Law can be applied to AGI systems to ensure that their actions promote balance and avoid harm. For example, an AGI system designed for healthcare must balance patient needs with resource availability, ensuring that decisions benefit society while maintaining fairness and equity. If the AGI violates this balance—say, by favoring one group over another—it could result in negative consequences, such as social inequality or resource misallocation. -/- Homeostasis in AGI Systems -/- Much like quantum systems, AGI must strive for homeostasis to maintain long-term operational stability. AGI should be able to detect imbalances in its decision-making process and correct them accordingly. For instance, an AGI operating in a financial system must adjust its strategies based on market feedback, ensuring that it consistently contributes to the stability of the market, without causing disruptive cycles. -/- Integrating Malicse’s Homeostasis Principle in AGI ensures that these systems are capable of continuous adaptation, balancing inputs and outputs in a way that prevents harmful outcomes. In decision-making, this means the AGI will always strive for balance, ensuring that no decision undermines the overall health of the system, whether it’s societal, economic, or environmental. -/- The Role of Education in Promoting Natural Balance -/- Educational systems are fundamental to shaping the leaders and innovators of the future. By incorporating the principles of natural balance, ethical decision-making, and feedback-based learning, we can produce individuals capable of understanding the complexities of quantum systems and AGI. -/- Malicse’s universal formula should be integrated into the educational curriculum at all levels, fostering a generation of thinkers who can balance cause and effect, understand feedback loops, and navigate the ethical challenges of technology. Through this holistic education, students will be better equipped to understand and contribute to the design of future technologies, ensuring that they maintain harmony with natural systems and societal needs. -/- Conclusion -/- Angelito Malicse’s universal formula offers a profound framework for understanding the fundamental principles of decision-making, both in human and computational systems. By integrating these principles into the design of quantum computers and AGI systems, we can create technologies that adhere to the natural laws of balance and ethics, preventing harmful outcomes and ensuring stable, sustainable progress. -/- In the realms of quantum computing and AGI, the application of the Law of Karma, Homeostasis, and Ethical Decision-Making will ensure that these advanced systems work in harmony with their environments, just as natural systems do. Further, by embedding these principles into educational curricula, we can train future generations to harness the power of these technologies in a way that benefits society, promotes fairness, and sustains the natural balance of the universe. -/- By applying Malicse’s universal formula across these domains, we can foster a future where technology and humanity work together in a sustainable, ethical, and balanced way. -/- . (shrink)

The standard formalism of quantum theory is derived by analyzing the behavior of single-variable physical systems. These systems, which have a minimal information capacity of only one piece of information, exhibit indeterministic behavior under independent measurements but can be described probabilistically for dependent measurements. By enforcing the principle of probability conservation in the transformations of outcome probabilities across various measurement scenarios, we derive the core components of standard quantum theory, including the Born rule, the Hilbert space structure, and the Schrödinger (...) equation. Furthermore, we demonstrate that the requirements for conducting quantum experiments – specifically, preparing physical systems in coherent states – effectively reduce the number of independent variables to one, thereby transforming these systems into single-variable ones in practice. This completes our first-principles, information-theoretic derivation of quantum theory as the physics of single-variable physical systems. (shrink)

This paper briefly outlines some advancements in paraconsistent logics for modelling knowledge representation and reasoning. Emphasis is given on the so-called Logics of Formal Inconsistency (LFIs), a class of paraconsistent logics that formally internalize the very concept(s) of consistency and inconsistency. A couple of specialized systems based on the LFIs will be reviewed, including belief revision and probabilistic reasoning. Potential applications of those systems in the AI area of KRR are tackled by illustrating some examples that emphasizes the importance (...) of a fine-tuned treatment of consistency in modelling reputation systems, preferences, argumentation, and evidence. (shrink)

Contextuality and entanglement are valuable resources for quantum computing and quantum information. Bell inequalities are used to certify entanglement; thus, it is important to understand why and how they are violated. Quantum mechanics and behavioural sciences teach us that random variables ‘measuring’ the same content (the answer to the same Yes or No question) may vary, if ‘measured’ jointly with other random variables. Alice’s and Bob’s raw data confirm Einsteinian non-signaling, but setting dependent experimental protocols are used to create samples (...) of coupled pairs of distant ±1 outcomes and to estimate correlations.Marginal expectations, estimated using these final samples, depend on distant settings. Therefore,a system of random variables ‘measured’ in Bell tests is inconsistently connected and it should be analyzed using a Contextuality- by-Default approach, what is done for the first time in this paper.The violation of Bell inequalities and inconsistent connectedness may be explained using a contextual locally causal probabilistic model in which setting dependent variables describing measuring instruments are correctly incorporated. We prove that this model does not restrict experimenters` freedom of choice which is a prerequisite of science. Contextuality seems to be the rule and not an exception; thus, it should be carefully tested. (shrink)

This doctoral dissertation investigates the notion of physical necessity. Specifically, it studies whether it is possible to account for non-accidental regularities without the standard assumption of a pre-existent set of governing laws. Thus, it takes side with the so called deflationist accounts of laws of nature, like the humean or the antirealist. The specific aim is to complement such accounts by providing a missing explanation of the appearance of physical necessity. In order to provide an explanation, I recur to fields (...) that have not been appealed to so far in discussions about the metaphysics of laws. Namely, I recur to complex systems’ theory, and to the foundations of statistical mechanics. The explanation proposed is inspired by how complex systems’ theory has elucidated the way patterns emerge, and by the probabilistic explanations of the 2nd law of thermodynamics. More specifically, this thesis studies how some constraints that make no direct reference to the dynamics can be a sufficient condition for obtaining in the long run, with high probability, stable regular behavior. I hope to show how certain metaphysical accounts of laws might benefit from the insights achieved in these other fields. According to the proposal studied in this thesis, some regularities are not accidental not in virtue of an underlying physical necessity. The non-accidental character of certain regular behavior is only due to its overwhelming stability. Thus, from this point of view the goal becomes to explain the stability of temporal patterns without assuming a set of pre-existent guiding laws. It is argued that the stability can be the result of a process of convergence to simpler and stable regularities from a more complex lower level. According to this project, if successful, there would be no need to postulate a (mysterious) intermediate category between logical necessity and pure contingency. Similarly, there would be no need to postulate a (mysterious) set of pre-existent governing laws. Part I of the thesis motivates part II, mostly by arguing why further explanation of the notions of physical necessity and governing laws should be welcomed (chapter 1), and by studying the plausibility of a lawless fundamental level (chapters 2 and 3). Given so, part II develops the explanation of formation of simpler and stable behavior from a more complex underlying level. (shrink)

Quantum-Based Consciousness Through the Universal Law of Balance -/- By Angelito Enriquez Malicse -/- Introduction -/- The nature of consciousness remains one of the most profound mysteries in science and philosophy. Traditional approaches, from Cartesian dualism to modern neuroscience, have attempted to explain consciousness as either separate from or entirely reducible to physical processes. However, neither classical physics nor standard cognitive science fully captures the depth of subjective experience. -/- Recent developments in quantum mechanics suggest that consciousness may emerge from (...) fundamental quantum processes. This perspective aligns with my Universal Law of Balance, which asserts that all natural phenomena—including human cognition—follow an inherent equilibrium. If the universe operates under a universal balancing principle, then consciousness itself must arise from a quantum-level equilibrium between mind, body, and environment. -/- In this essay, I propose a Quantum-Based Consciousness Model grounded in the Universal Law of Balance. This model bridges quantum physics, homeostasis, and the dynamic feedback systems that regulate conscious awareness. -/- 1. The Mind-Body Problem and Quantum Balance -/- The traditional mind-body problem questions how the subjective experience of consciousness arises from material processes. Classical neuroscience views the brain as a computational machine, where neural activity produces cognition through deterministic or probabilistic functions. However, this classical approach fails to explain: -/- Quantum Indeterminacy in Neural Activity – Brain function exhibits micro-level quantum behavior, which may be integral to decision-making and perception. -/- The observer Effect – Consciousness appears to interact with reality at a fundamental level, as seen in quantum experiments like the double-slit experiment. -/- Non-Locality and Entanglement – Human thought processes may exhibit quantum-like non-locality, where ideas, emotions, and memories interact in ways that classical physics cannot fully describe. -/- Applying the Universal Law of Balance -/- According to my Universal Law of Balance, all natural processes—including cognition—maintain a homeostatic equilibrium. Consciousness does not arise from material processes alone but from a quantum-based equilibrium that continuously stabilizes the interaction between: -/- 1. Physical Processes (Neural and biological systems) -/- 2. Quantum Fields (Subatomic processes in brain microtubules and electromagnetic fields) -/- 3. Environmental Feedback (Sensory input, social interaction, and external conditions) -/- When these three components are in balance, a stable conscious experience emerges. Disruptions in this balance—such as mental illness, stress, or sensory overload—disturb consciousness, leading to cognitive dysfunction. -/- 2. Quantum Coherence and the Emergence of Consciousness -/- One possible explanation for consciousness in quantum mechanics is quantum coherence—the idea that subatomic particles remain in a superposition until observed. In the brain, microtubules (tiny structures within neurons) may maintain quantum coherence, allowing for complex, non-linear processing. This is the foundation of Roger Penrose and Stuart Hameroff’s Orchestrated Objective Reduction (Orch-OR) Theory. -/- However, my Universal Law of Balance refines this concept by proposing that consciousness emerges when quantum coherence reaches a dynamic equilibrium with classical neural processes. This means: -/- Consciousness is neither fully deterministic (as in classical physics) nor purely random (as in quantum indeterminacy). Instead, it stabilizes at a balanced point where quantum effects interact with large-scale neural activity. -/- The collapse of the wave function in microtubules is not purely random but governed by a natural equilibrium, ensuring cognitive stability. -/- This equilibrium mechanism aligns with homeostasis in biological systems, where the mind continuously adjusts to maintain stable awareness. -/- 3. Feedback Mechanisms in Conscious Decision-Making -/- The Universal Law of Balance suggests that all decision-making follows a feedback system between internal cognition and external reality. This aligns with quantum theory’s concept of entanglement, where particles remain correlated across distances. -/- Consciousness as a Quantum Feedback Loop -/- 1. Perception (Quantum Input) – Sensory data enters the brain and is processed at both the classical (neuronal) and quantum (wave-function) levels. -/- 2. Processing (Balance Point) – The brain stabilizes this input, maintaining a balance between deterministic neural patterns and quantum superpositions. -/- 3. Decision-Making (Quantum Collapse and Output) – Conscious action occurs when the brain collapses quantum possibilities into a stable outcome. -/- This cycle mirrors the homeostatic feedback present in all biological systems. Just as the body regulates temperature or glucose levels to maintain balance, consciousness regulates perception and decision-making to maintain cognitive equilibrium. -/- 4. Implications for Artificial Intelligence and AGI -/- If human consciousness follows a quantum-based balance mechanism, then creating true Artificial General Intelligence (AGI) requires integrating this principle. Current AI systems function purely on classical computation and lack quantum equilibrium. However, a future AGI system designed with: -/- Quantum computing components -/- Real-time homeostatic feedback -/- Self-regulating decision models -/- …could mimic human-like consciousness. This aligns with my belief that future AI should follow the Universal Law of Balance to achieve true intelligence. -/- 5. Conclusion: A Balanced Consciousness Model -/- Quantum-based consciousness is best understood through the Universal Law of Balance, which integrates: -/- Quantum Mechanics – Superposition, coherence, and wave function collapse shape cognitive states. -/- Neuroscience – The brain maintains a balance between quantum and classical processes. -/- Environmental Feedback – Consciousness is a dynamic, homeostatic system that adjusts to internal and external conditions. -/- By applying this principle, we bridge physics, biology, and philosophy, offering a unified framework for understanding consciousness. This balance-driven model could revolutionize fields like cognitive science, mental health, and AI development, guiding humanity toward a deeper comprehension of its own nature. -/- . (shrink)

Based on Kolchinsky and Wolpert’s work on the semantics of autonomous agents, I propose an application of Mathematical Logic and Probability to model cognitive processes. In this work, I will follow Bateson’s insights on the hierarchy of learning in complex organisms and formalize his idea of applying Russell’s Type Theory. Following Weaver’s three levels for the communication problem, I link the Kolchinsky–Wolpert model to Bateson’s insights, and I reach a semantic and conceptual hierarchy in living systems as an explicative model (...) of some adaptive constraints. Due to the generality of Kolchinsky and Wolpert’s hypotheses, I highlight some fundamental gaps between the results in current Artificial Intelligence and the semantic structures in human beings. In light of the consequences of my model, I conclude the paper by proposing a general definition of knowledge in probabilistic terms, overturning de Finetti’s Subjectivist Definition of Probability. (shrink)

The paper develops a classificatory system of basic argument types on the basis of the epis-temological approach to argumentation. This approach has provided strict rules for several kinds of argu-ments. These kinds may be brought into a system of basic irreducible types, which rely on different parts of epistemology: deductive logic, probability theory, utility theory. The system reduces a huge mass of differ-ent argument schemes to basic types and gives them an epistemological foundation.

Bayesian cognitive science is a research programme that relies on modelling resources from Bayesian statistics for studying and understanding mind, brain, and behaviour. Conceiving of mental capacities as computing solutions to inductive problems, Bayesian cognitive scientists develop probabilistic models of mental capacities and evaluate their adequacy based on behavioural and neural data generated by humans (or other cognitive agents) performing a pertinent task. The overarching goal is to identify the mathematical principles, algorithmic procedures, and causal mechanisms that enable cognitive (...) agents to take uncertainty into account and weigh it appropriately in producing adaptive behaviour. -/- The appeal of Bayesian cognitive science derives from its transparency, normativity, and unifying power. Resources from Bayesian statistics allow cognitive scientists to characterise transparently, in terms of random variables and probabilistic dependencies between them, the inductive problems that many mental capacities are presumed to solve. Given this characterisation, researchers can define an upper bound on one’s performance on that problem and use it as a benchmark for interpreting experimental results, formulating hypotheses about why and when deviations from optimal performance should be expected, and seeking explanations of mental capacities within one encompassing theoretical framework. -/- Although critics question the testability, explanatory power, and plausibility of Bayesian models of mental capacities, Bayesian cognitive science has proved itself to be an incredibly fruitful research programme. Fuelled by empirical and theoretical results from psychology, neuroscience, philosophy, computer science, artificial intelligence, and evolution, Bayesian cognitive science has: advanced our understanding of why cognitive systems should keep track of uncertainty and use it to facilitate adaptive behaviour; clarified how the brain might encode information about the uncertainty of its stimuli and perform computations with probability distributions; and crystallised the insight that cognitive agents’ management of uncertainty might be grounded in predictive processes aimed at avoiding surprising exchanges with the environment. (shrink)

We propose a typology of representational artifacts for health care and life sciences domains and associate this typology with different kinds of formal ontology and logic, drawing conclusions as to the strengths and limitations for ontology in a description logics framework. The four types of domain representation we consider are: (i) lexico-semantic representation, (ii) representation of types of entities, (iii) representations of background knowledge, and (iv) representation of individuals. We advocate a clear distinction of the four kinds of representation in (...) order to provide a more rational basis for using ontologies and related artifacts to advance integration of data and enhance interoperability of associated reasoning systems. We highlight the fact that only a minor portion of scientifically relevant facts in a domain such as biomedicine can be adequately represented by formal ontologies as long as the latter are conceived as representations of entity types. In particular, the attempt to encode default or probabilistic knowledge using ontologies so conceived is prone to produce unintended, erroneous models. (shrink)

Reasoning over our knowledge bases and theories often requires non-deductive inferences, especially – but by no means only – when commonsense reasoning is the case, i.e. when practical agency is called for. This kind of reasoning can be adequately formalized via the notion of supraclassical consequence, a non-deductive consequence tightly associated with default and non-monotonic reasoning and featuring centrally in abductive, inductive, and probabilistic logical systems. In this paper, we analyze core concepts and problems of these systems in the (...) light of supraclassical consequence. (shrink)

As a moral foundation for vegetarianism and other consumer choices, act consequentialism can be appealing. When we justify our consumer and dietary choices this way, however, we face the problem that our individual actions rarely actually precipitate more just agricultural and economic practices. This threshold or individual impotence problem engaged by consequentialist vegetarians and their critics extends to morally motivated consumer decision-making more generally, anywhere a lag persists between individual moral actions taken and systemic moral progress made. Regan and others (...) press just this point against Singer's utilitarian basis for vegetarianism; recently Chartier criticizes act-consequentialist vegetarianism by identifying many factors weakening the connection between individual meat purchases and changes in animal production. While such factors are relevant to act-consequentialist moral reasoning, I argue, they need not defeat the act-consequentialist case for vegetarianism and consumer ethics. This is shown by offering a probabilistic account of the threshold issue and discussing the positive and negative role-modelling effects of our morally motivated dietary and consumer choices. (shrink)

Background Men with antisocial personality disorder show lifelong abnormalities in adaptive decision making guided by the weighing up of reward and punishment information. Among men with antisocial personality disorder, modifi cation of the behaviour of those with additional diagnoses of psychopathy seems particularly resistant to punishment. Methods We did a case-control functional MRI (fMRI) study in 50 men, of whom 12 were violent off enders with antisocial personality disorder and psychopathy, 20 were violent off enders with antisocial personality disorder but (...) not psychopathy, and 18 were healthy non-off enders. We used fMRI to measure brain activation associated with the representation of punishment or reward information during an event-related probabilistic response-reversal task, assessed with standard general linear-model-based analysis. Findings Offenders with antisocial personality disorder and psychopathy displayed discrete regions of increased activation in the posterior cingulate cortex and anterior insula in response to punished errors during the task reversal phase, and decreased activation to all correct rewarded responses in the superior temporal cortex. This finding was in contrast to results for off enders without psychopathy and healthy non-off enders. Interpretation Punishment prediction error signalling in off enders with antisocial personality disorder and psychopathy was highly atypical. This finding challenges the widely held view that such men are simply characterised by diminished neural sensitivity to punishment. Instead, this fi nding indicates altered organisation of the information processing system responsible for reinforcement learning and appropriate decision making. This difference between violent offenders with antisocial personality disorder with and without psychopathy has implications for the causes of these disorders and for treatment approaches. (shrink)

In this work we present NERVOUS, an intelligent recommender system exploiting a probabilistic extension of a Description Logic of typicality to dynamically generate novel contents in AllMusic, a comprehensive and in-depth resource about music, providing data about albums, bands, musicians and songs. The tool can be used for both the generation of novel music genres and styles, described by a set of typical properties characterizing them, and the reclassification of the available songs within such new genres.

Inventing novel knowledge to solve problems is a crucial, creative, mechanism employed by humans, to extend their range of action. In this paper, we present TCL (typicality-based compositional logic): a probabilistic, non monotonic extension of standard Description Logics of typicality, and will show how this framework is able to endow artificial systems of a human-like, commonsense based, concept composition procedure that allows its employment in a number of applications (ranging from computational creativity to goal-based reasoning to recommender systems and (...) affective computing). -/- The framework relies on 3 main ingredients: a non monotonic extension of standard Description Logics (allowing to reason on exceptions to inheritance in standard knowledge bases) a probabilistic extension coming from the field of logic programming (the DISPONTE semantics) a cognitive heuristics known ad HEAD-Modifier determining preference rules for the inheritance mechanisms of the novel concepts to be generated via commonsense rules. -/- We report the obtained results and the lessons learned of this research path in the context of model-based AI applications. -/- . (shrink)

In this work we present an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework (i.e. the TCL logic, see Lieto & Pozzato 2020) which is based on a human-like procedure for the automatic generation of novel concepts in a Description Logics knowledge base (see also Lieto et al. 2019, Chiodino et al. 2020 for other applications). In particular, in order to model human-like forms (...) of concept combinations, the TCL logic combines a probabilistic description logics of typicality with the HEAD-MODIFIER heuristics coming from cognitive semantics. In the context of our application of such framework, our system exploits the logic TCL to automatically generate novel commonsense semantic representations of compound emotions (e.g. Love as derived from the combination of Joy and Trust according to Plutchik’s theory of emotions, see Plutchik 2001). The generated emotions corresponds to prototypes, i.e. commonsense representations of given concepts, and have been used to reclassify emotion-related contents in a variety of artistic domains. We have tested our system in the context of the H2020 EU project SPICE for providing artistic recommendations of museum items in the Galleria di Arte Moderna (GAM) of Turin. The obtained results (reported in Lieto et al, 2021 and Lieto at al., to appear) show promising results for what concerns both the acceptance of the provided affective recommendation and the explainability associated to each suggestion made by the users. Here we discuss, the open problems and the lessons learned. -/- . (shrink)

In quantum theory every state can be diagonalized, i.e. decomposed as a convex combination of perfectly distinguishable pure states. This elementary structure plays an ubiquitous role in quantum mechanics, quantum information theory, and quantum statistical mechanics, where it provides the foundation for the notions of majorization and entropy. A natural question then arises: can we reconstruct these notions from purely operational axioms? We address this question in the framework of general probabilistic theories, presenting a set of axioms that guarantee (...) that every state can be diagonalized. The first axiom is Causality, which ensures that the marginal of a bipartite state is well defined. Then, Purity Preservation states that the set of pure transformations is closed under composition. The third axiom is Purification, which allows to assign a pure state to the composition of a system with its environment. Finally, we introduce the axiom of Pure Sharpness, stating that for every system there exists at least one pure effect occurring with unit probability on some state. For theories satisfying our four axioms, we show a constructive algorithm for diagonalizing every given state. The diagonalization result allows us to formulate a majorization criterion that captures the convertibility of states in the operational resource theory of purity, where random reversible transformations are regarded as free operations. (shrink)

Abstract: This paper endeavors to establish a comprehensive account of human knowledge that embraces the probabilistic nature of truth, the integral role of language in our cognitive processes, and the uncertainty and fallibility inherent in our cognitive systems. Drawing upon the work of various philosophers, psychologists, and neuroscientists, the paper advocates for a reinterpretation of the traditional "Justified True Belief" as "Justified Probable Belief." Additionally, the biological underpinnings of this perspective are explored, with an emphasis on synaptic plasticity, dopamine-based (...) learning, and epigenetic mechanisms. (shrink)

Complex logic is a novel logical framework, which formalizes the semantics of the categories of matter, space, and time in a system of logic that operates with complex logical objects. A complex logical object represents a superposition of a logical statement and its logical negation positioning any statement co-relatively to its logical negation. In the system of logical notations, where S is a logical statement and Not S is its logical negation, complex logic includes co-relative logical positions of (...) S and Not S with the probabilities of their truth within the scale 0... 1, excluding the boundary values of 0 and 1, into a single logical superposition. Thus, the logical superposition, summing up the probabilistic positions of S and Not S, has an invariant truth value equal to 1. In this context, complex logic proves to be invariant to reality, offering a unified logical interpretation of reality, spanning from quantum to cosmological scales. By defining the nature of matter and reality as a complex two-format processual essence with corresponding logical consequences, complex logic enhances our concept and understanding of reality. (shrink)

The Wave Function Collapse Explained Through the Universal Formula of Balance in Nature -/- The wave function collapse, a concept within quantum mechanics, describes how a quantum system transitions from a state of superposition—where it exists in multiple possible states simultaneously—into a single, definite state when observed or measured. This phenomenon, integral to understanding quantum behavior, can be examined through the lens of the Universal Formula of Balance in Nature, which underlies all human and natural decision-making. By applying the (...) three laws of this formula, we can gain insight into how the wave function collapse operates as part of the larger web of interconnected systems, governed by balance. -/- The First Law: The Law of Karma and Systems -/- The first law of the Universal Formula is the law of karma, which encompasses the idea that every action or event is part of a system of cause and effect. This law emphasizes that systems, whether natural or man-made, must function without defects to achieve balance and harmony. When applied to the wave function collapse, this law explains that a quantum system, much like any other system, requires a point of resolution—a collapse—when its probabilistic superposition is observed. This is not random, but a necessary result of the system’s inherent need to resolve into a singular state to preserve the integrity of the system itself. -/- In quantum mechanics, the wave function represents a superposition of all possible states of a system, each with a certain probability. The law of karma suggests that, in the context of the quantum system, each of these possibilities is a part of a larger, interconnected reality. When the system is measured, the inherent demand for balance causes it to collapse into a definite state, eliminating any internal defects or contradictions. This collapse is not arbitrary; it is the manifestation of the need for coherence and resolution within the quantum system, much like how a faulty part in a machine will result in malfunction until it is fixed. -/- The Second Law: The Law of Feedback Mechanisms -/- The second law of the Universal Formula is the law of feedback, which highlights the influence of interconnected feedback loops between systems. In the context of quantum mechanics, feedback mechanisms play a crucial role in shaping the outcomes of quantum measurements. The act of measurement itself can be seen as an external feedback loop that forces the wave function to collapse into a specific state. This aligns with the idea that observation influences the system, and the collapse is a necessary response to this interaction. -/- Quantum systems, much like the human mind in decision-making, exist in constant interaction with their environment. The collapse can be understood as the system’s way of reconciling its internal probabilities with external influences. The observer’s role introduces an external feedback loop that forces the wave function to resolve into a state that aligns with the feedback, just as individuals make decisions based on feedback from their surroundings, adjusting their behavior accordingly. The collapse, then, is a response to this larger dynamic of influence between the system and the observer. -/- The Third Law: The Law of Balance -/- The third law of the Universal Formula is the law of balance, which dictates that all natural systems strive for equilibrium, and that imbalance leads to disorder and dysfunction. This law serves as the key to understanding why wave function collapse happens in the first place. The wave function represents an array of possibilities, each contributing to a probabilistic state. However, for the system to operate coherently, it must resolve into one of these possibilities, restoring balance within the system. -/- Without the collapse, the quantum system would remain in an indeterminate state, creating a form of disorder where the potential states conflict with one another. The collapse brings the system into a balanced, observable state, which is necessary for the functioning of both the quantum system and the larger universe. In this sense, the collapse can be seen as the system’s inherent tendency to restore balance, just as an individual mind seeks harmony by making decisions that align with natural laws. -/- Conclusion -/- When viewed through the Universal Formula of Balance in Nature, the wave function collapse is not a mysterious or unpredictable event, but a natural consequence of the laws that govern all systems—both quantum and classical. The first law of karma ensures that any system, including quantum systems, must be free of defects to function correctly. The second law of feedback highlights the role of external influences in forcing the system to resolve, while the third law of balance underscores the need for the system to collapse into a definite state to maintain harmony. Together, these principles provide a holistic understanding of the wave function collapse, integrating it into the broader framework of natural law and reinforcing the interconnectedness of all systems in the universe. -/- Through this lens, the collapse of the wave function becomes an essential part of the process by which the universe maintains order and coherence, just as individuals and societies must make decisions in alignment with the natural laws of balance to foster harmony and progress. -/- . (shrink)

This paper proposes a novel framework for understanding consciousness as a dynamic navigator of parallel realities, guided by principles of least-action optimization akin to the brachistochrone curve in physics. Rather than moving linearly through time, consciousness may instead be selecting optimal trajectories across a pre-existing structure of potential realities, ensuring continuity and coherence in perceived experience. By drawing parallels to quantum wavefunction collapse, black hole thermodynamics, and Hawking radiation, we explore how dreams may function as a subconscious dissipation mechanism, offloading (...) unresolved cognitive mass in a manner analogous to radiation leakage from a black hole. Furthermore, computational models suggest that consciousness does not select realities randomly but instead follows an energy-minimizing trajectory, favoring paths of least resistance in a way consistent with Lagrangian mechanics and the Euler-Lagrange equation. These findings suggest that reality is not a fixed sequence of events but rather a fluid system of probabilistic timeline selection, where awareness, intention, and subconscious processes influence the unfolding trajectory of experience. This theory provides a new perspective on dreams, time perception, and the mechanics of reality navigation, inviting further exploration into whether consciousness can actively refine its trajectory through directed awareness and mental training techniques. (shrink)