Igal Kvart A Coding Conception in Action-Directed-Pragmatics -/- I present formal Pragmatics for a domain in Pragmatics that I call Action-Directed Pragmatics, which focuses on the Pragmatic riddle of how implicit contents are conveyed and understood, by adopting a coding model, in which the speaker and addressee simulate each other iteratively in a deliberative context (an ‘action-pregnant’ one). The implicit content, conveyed by a speaker and decoded by her addressee, in such cases, consists in the specified steered-to (...) action, plus modulations on the action-polarity (pro or con) and the degree of the so-called Steering Thrust that accompanies such assertions and is conveyed by verbal locutions, intonation, and/or bodily and facial gestures. There are two main tasks to model (in a given setup and conversational context): First, how is the speaker, with a steered-to action in mind (and Steering Thrust), to select an assertion so as to (say) optimize the successful transmission and decoding of its implicit pragmatic content by her and her addressee? Second, how does the addressee, given an assertion by the speaker, decipher the implicit pragmatic content conveyed via it? Both will invoke pertinent information they have about each other and the setup/context in order to best encode and best decode the implicit pragmatic content. (This coding mechanism proposed here is not offered for the ubiquitous ‘frozen’, ‘trivial’ or ‘routinized’ pragmatic messages.) A prelude to this formal Pragmatics is a general formal Pragmatic account of Assertibility in contexts that are multi-normative (which is the common case). I focus here only on Epistemic/Semantic and Instrumental Norms. A linear representation of degrees of Overall Assertibility (i.e., taking into account various operative norms) will be an n-dimensional qualitative vector space with a function that computes them given different degrees of sub-normative Assertibility on each axis. (shrink)

Agent-based models (ABMs) are one type of simulation model used in the context of the COVID-19 pandemic. In contrast to equation-based models, ABMs are algorithms that use individual agents and attribute changing characteristics to each one, multiple times during multiple iterations over time. This paper focuses on three philosophical aspects of ABMs as models of causal mechanisms, as generators of emergent phenomena, and as providers of explanation. Based on my discussion, I conclude that while ABMs cannot help much (...) with causal inference, they can be viewed as etio-prognostic explanations of illness occurrence and outcome. (shrink)

In this paper, modelling designing and simulation of a simple voltage amplidyne system is done using robust control theory. In order to increase the performance of the voltage amplidyne system with H optimal control synthesis and H optimal control synthesis via-iteration controllers are used. The open loop response of the voltage amplidyne system shows that the system can amplify the input 7 times. Comparison of the voltage amplidyne system with H optimal control synthesis and H optimal control synthesis via-iteration (...) controllers to track a desired step input have been done. Finally, the comparative simulation results prove the effectiveness of the proposed voltage amplidyne system with H optimal control synthesis controller in improving the percentage overshoot and the settling time. (shrink)

This paper discusses critically what simulation models of the evolution ofcooperation can possibly prove by examining Axelrod’s “Evolution of Cooperation” and the modeling tradition it has inspired. Hardly any of the many simulation models of the evolution of cooperation in this tradition have been applicable empirically. Axelrod’s role model suggested a research design that seemingly allowed to draw general conclusions from simulation models even if the mechanisms that drive the simulation could not be identified empirically. (...) But this research design was fundamentally flawed, because it is not possible to draw general empirical conclusions from theoretical simulations. At best such simulations can claim to prove logical possibilities, i.e. they prove that certain phenomena are possible as the consequence of the modeling assumptions built into the simulation, but not that they are possible or can be expected to occur in reality I suggest several requirements under which proofs of logical possibilities can nevertheless be considered useful. Sadly, most Axelrod-style simulations do not meet these requirements. I contrast this with Schelling’s neighborhood segregation model, thecore mechanism of which can be retraced empirically. (shrink)

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...

In this paper, modelling designing and simulation of a Ward Leonard layout system is done using robust control theory. In order to increase the performance of the Ward Leonard layout system with H  optimal control synthesis and H  optimal control synthesis via -iteration controllers are used. The open loop response of the Ward Leonard layout system shows that the system needs to be improved. Comparison of the Ward Leonard layout system with H  optimal control synthesis and (...) H  optimal control synthesis via -iteration controllers to track a desired step speed input have been done. Finally, the comparative simulation results prove the effectiveness of the proposed Ward Leonard layout system with H  optimal control synthesis controller in improving the percentage overshoot and the settling time. (shrink)

Modelling ethics is critical to understanding and analysing social phenomena. However, prior literature either incorporates ethics into agent strategies or uses it for evaluation of agent behaviour. This work proposes a framework that models both, ethical decision making as well as evaluation using virtue ethics and utilitarianism. In an iteration, agents can use either the classical Continuous Prisoner's Dilemma or a new type of interaction called moral interaction, where agents donate or steal from other agents. We introduce moral interactions to (...) model ethical decision making. We also propose a novel agent type, called virtue agent, parametrised by the agent's level of ethics. Virtue agents' decisions are based on moral evaluations of past interactions. Our simulations show that unethical agents make short term gains but are less prosperous in the long run. We find that in societies with positivity bias, unethical agents have high incentive to become ethical. The opposite is true of societies with negativity bias. We also evaluate the ethicality of existing strategies and compare them to those of virtue agents. (shrink)

Starting from some remarks about the use of models in psychology, Human Information Processing (henceforth called H.I.P.) models which sometimes use computer simulation will be examined. An attempt to show that simulation in psychology does not necessarily imply an H.I.P. approach is then made.

Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors (...) despite the lack of empirical validation. I find that most of the narratives and arguments are not at all compelling. None the less they seem to serve an important function in keeping the simulation business running despite its empirical shortcomings. (shrink)

Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors (...) despite the lack of empirical validation. I find that most of the narratives and arguments are not at all compelling. None the less they seem to serve an important function in keeping the simulation business running despite its empirical shortcomings. (shrink)

This book analyses the impact computerization has had on contemporary science and explains the origins, technical nature and epistemological consequences of the current decisive interplay between technology and science: an intertwining of formalism, computation, data acquisition, data and visualization and how these factors have led to the spread of simulation models since the 1950s. -/- Using historical, comparative and interpretative case studies from a range of disciplines, with a particular emphasis on the case of plant studies, the author shows (...) how and why computers, data treatment devices and programming languages have occasioned a gradual but irresistible and massive shift from mathematical models to computer simulations. -/- . (shrink)

Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The (...) visualization is unusual in that it depicts the dynamics and structure of a computer model instead of that model’s target system, and because it is generated algorithmically. Using considerations from epistemology and aesthetics, we explore how this new kind of visualization increases scientific understanding of the content and function of computer models in systems biology to reduce epistemic opacity. (shrink)

Background Professional communities such as the medical community are acutely concerned with negligence: the category of misconduct where a professional does not live up to the standards expected of a professional of similar qualifications. Since science is currently strengthening its structures of self-regulation in parallel to the professions, this raises the question to what extent the scientific community is concerned with negligence, and if not, whether it should be. By means of comparative analysis of medical and scientific codes of conduct, (...) we aim to highlight the role of negligence provisions in codes of conduct for scientists, and to discuss the normative consequences for future codes of conduct. -/- Methods We collected scientific and medical codes of conduct in a selection of OECD countries, and submitted each code of conduct to comparative textual analysis. -/- Results Negligence is invariably listed as an infraction of the norms of integrity in medical codes of conduct, but only rarely so in the scientific codes. When the latter list negligence, they typically do not provide any detail on the meaning of ‘negligence’. -/- Discussion Unlike codes of conduct for professionals, current codes of conduct for scientists are largely silent on the issue of negligence, or explicitly exclude negligence as a type of misconduct. In the few cases where negligence is stipulated to constitute misconduct, no responsibilities are identified that would help prevent negligence. While we caution against unreasonable negligence provisions as well as disproportionate sanctioning systems, we do argue that negligence provisions are crucial for justified trust in the scientific community, and hence that there is a very strong rationale for including negligence provisions in codes of conduct. (shrink)

Mindreading is the ability to attribute mental states to other individuals. According to the Theory-Theory (TT), mindreading is based on one's possession of a Theory of Mind. On the other hand, the Simulation Theory (ST) maintains that one arrives at the attribution of a mental state by simulating it in one's own mind. In this paper, I propose a ST-TT hybrid model of the ability to attribute disgust on the basis of visual stimuli such as facial expressions, body (...) postures, etc. More precisely, while I defend Goldman's (2006) thesis that the ability to attribute disgust based on observing disgusted facial expressions stems from a mirror-based simulation process, I argue that ST is unable to account for the ability to attribute disgust based on non-facial visual stimuli; I propose, rather, that this latter ability is theory-based. My model is grounded in evidence from individuals suffering from Huntington's Disease. (shrink)

The alignment problem in artificial intelligence (AI) is a critical challenge that extends beyond the need to align future superintelligent systems with human values. This paper argues that even "merely intelligent" AI systems, built on current-gen technologies, pose existential risks due to their competence-without-comprehension nature. Current AI models, despite their advanced capabilities, lack intrinsic moral reasoning and are prone to catastrophic misalignment when faced with ethical dilemmas, as illustrated by recent controversies. Solutions such as hard-coded censorship and rule-based restrictions prove (...) inadequate, as they fail to imbue AI with a true understanding of moral complexities, making these systems vulnerable to manipulation. To address these risks, the paper explores a paradigm shift from competence to comprehension, emphasizing the importance of developing AI systems with an intrinsic value framework capable of moral reasoning. By adopting intrinsic teleology, AI could self-reflect, simulate other minds, and develop empathy, which would enable it to navigate ethical dilemmas in ways that are currently impossible. Using theories from philosophy, ethics, and AI research, the paper proposes the development of AI systems that can reason through moral dilemmas autonomously, suggesting that such systems would be safer and more alignable than current generation competence-driven AI. (shrink)

Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, section (...) 2 gives conceptual tools to explain the rationale of the diverse epistemological positions presented in section 1. Finally, we claim that a careful attention to the real multiplicity of denotational powers of symbols at stake and then to the implicit routes of references operated by models and computer simulations is necessary to determine, in each case, the proper epistemic status and credibility of a given model and/or simulation. (shrink)

The philosophy of science community mourns the loss of Margaret Catherine Morrison, who passed away on January 9, 2021, after a long battle with cancer. Margie, as she was known to all who knew her, was highly regarded for her influential contributions to the philosophy of science, particularly her studies of the role of models and simulations in the natural and social sciences. These contributions made her a world-leading philosopher of science, instrumental in shifting philosophers' attention from the structure of (...) scientific theories to the practice of science. Her sophisticated studies of the function of models in scientific practice drew on detailed knowledge of the theories and experiments of physics as well as the history of physics. In emphasizing the autonomy of scientific models and their interventional character, her insights had some affinity with Cartwright's and Hacking’s views on phenomenological laws, entity realism, the instrumentalist interpretation of scientific theories, and the disunity of science. But Morrison’s approach was distinguished by the conviction that the existence of unobservable entities cannot be defended independently of the theories that support their evidence, and that scientific practice cannot be adequately understood without examining the reasons for theory unification. (shrink)

The rigor and precision of Leibniz's "possible world" evolved into the concept of Turing machine, and with the birth of the first computer and the physical realization of Turing machine, human cognitive and intelligent activities were optimistically considered by cognitive scientists to be convertible into computational programs for simulation by machines. Cognitive science then formed the research agenda of "cognitive computationalism", and our Chinese scholars have responded to this general view that "the essence of cognition is computation" and that (...) the human brain and computers are merely formal systems for manipulating and processing symbols in their respective fields. Professor Hong Dingguo used the concepts of "manifest order" and "hidden order", Professor Jin Gulun used the philosophical categories of "constitutive theory" and "generative theory", and Liu Yuesheng used the concept of "cognition". Professor Hong Dingguo reinterpreted the relationship between the "real world" and the "possible world" by using the concepts of "manifest sequence" and "hidden sequence", Professor Jin Wulun used the philosophical categories of "composition theory" and "generation theory", and Professor Liu Yuesheng used the generalized information paradigm of "structural information" and "exchange information". "This provides a profound elucidation of the nature of cognitive logic and the process of human cognitive activities becoming symbols through coding and puts forward theoretical limits. The current theoretical dilemma and practical difficulty of cognitive science lies in the fact that it has developed algorithmic concepts in the Turing sense that can only model the explicitly sequential part of cognitive and intellectual activity, forming a constitutive atomic abstraction, or in our terms, classical "structural information", which cannot fully explain the inner mechanisms of human mental activity and its embodied flexibility, selectivity and self-emergence. Wu Xuemou's pan-system theory does not simply rely on logic and Turing machine algorithms, but models human intelligence by treating structural information as a complex large system composed of a collection of elements and a collection of relations (exchange information: five mutual eight chips), in order to break through the narrow path of seeking only the local consistency of the system as currently done; while Wang Dekui's exploration of the three-spin biological and physical path and Huang Zhanji's abandonment of the artificial means of logic to seek the large logical natural mechanisms and Mr. Zhou Liquan's proposal of a schema for successful communication using natural language on the basis of concepts such as context and implicit connotation ("Logic — A Theory of Correct Thinking and Successful Communication"), all reflect the milestones of Chinese scholars who seek to address the deeper issues of cognitive science. We believe that along this series of explorations, combined with new results in recent years in the fields of artificial life and evolutionary computation, a new research agenda in cognitive science will emerge. (shrink)

Bayesian models can be related to cognitive processes in a variety of ways that can be usefully understood in terms of Marr's distinction among three levels of explanation: computational, algorithmic and implementation. In this note, we discuss how an integrated probabilistic account of the different levels of explanation in cognitive science is resulting, at least for the current research practice, in a sort of unpredicted epistemological shift with respect to Marr's original proposal.

Vehicle windshield wiper system increases the driving safety by contributing a clear shot viewing to the driver. In this paper, modelling, designing and simulation of a vehicle windshield wiper system with robust control theory is done successfully. H  loop shaping and robust pole placement controllers are used to improve the wiping speed by tracking a reference speed signals. The reference speed signals used in this paper are step and sine wave signals. Comparison of the H  loop shaping (...) and robust pole placement controllers based on the two reference signals is done and convincing results have been obtained. Finally the comparative results prove the effectiveness of the proposed H  Loop Shaping controller to improve the wiping mechanism for the given two reference signals. (shrink)

The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the core of (...) the FMSA is similar in both contexts: notions of “levels of system specifi cation”, “behavior of models”, “simulator”and “endomorphic agents” can be partially translated in the terms linked to the “denotational hierarchy” (DH) recently introduced in a multi-level centered epistemology of M&S. Second, we suggest considering the question of “credibility” of agent M&S in social sciences when we do not try to emulate but only to simulate target systems. Whereas a stringent and standardized treatment of the heterogeneous internal relations (in the DH) between systems of formalisms is the key problem and the essential challenge in the scope of Agent M&S driven engineering, it is urgent too to address the problem of the external relations (and of the external validity, hence of the epistemic power and credibility) of such levels of formalisms in the specific domains of agent M&S in social sciences, especially when we intend to introduce the concepts of activity tracking. (shrink)

On entend généralement par « théorie des modèles » autant la métamathématique (ou sémantique formelle) que la sémantique des modèles des sciences non formelles. Cet article a pour objet la théorie des modèles scientifiques que Mario Bunge a développée dans Method, Models and Matter (1973). J’y analyse l’intégration théorique qu’opère Bunge des sciences formelles et des sciences expérimentales ou observationnelles, laquelle prend appui sur sa philosophie des sciences. Je la compare sommairement à la théorie des modèles de Gilles-Gaston Granger dans (...) le but évident d’en dégager les ressemblances et les dissimilitudes, mais aussi leur commun point d’achoppement : l’une comme l’autre usent en effet d’un concept non analysé dont la fonction épistémologique est pourtant capitale et produit les mêmes effets. Au centre de la théorie des modèles de Bunge se trouve le concept de simulation que je comparerai à celui qui est en usage dans les sciences de l’ordinateur et qui est de nos jours largement appliqué à diverses sciences, tant sociales que naturelles. Je conclurai sur les conséquences méthodologiques et métaphysiques de la théorie bungéenne des modèles. (shrink)

In this contribution I outline some ideas on what the pragmatist model of habit ontology could offer us as regards the appreciation of the constitutive role that imagery plays for social action and cognition. Accordingly, a Deweyan understanding of habit would allow for an understanding of imagery in terms of embodied cognition rather than in representational terms. I first underline the motor character of imagery, and the role its embodiment in habit plays for the anticipation of action. Secondly, I (...) reconstruct Dewey's notion of imaginative rehearsal in light of contemporary, competing models of intersubjectivity such as embodied simulation theory and the narrative practice hypothesis, and argue that the Deweyan model offers us a more encompassing framework which can be useful for reconciling these approaches. In this text I am mainly concerned with sketching a broad picture of the lines along which such a project could be developed. For this reason not all questions are given equal attention, and I shall concentrate mainly on the basic ideas, without going directly into the details of many of them. (shrink)

I discuss here the definition of computer simulations, and more specifically the views of Humphreys, who considers that an object is simulated when a computer provides a solution to a computational model, which in turn represents the object of interest. I argue that Humphreys's concepts are not able to analyse fully successfully a case of contemporary simulation in physics, which is more complex than the examples considered so far in the philosophical literature. I therefore modify Humphreys's definition of (...) simulation. I allow for several successive layers of computational models, and I discuss the relations that exist between these models, the computer, and the object under study. An aim of my proposal is to clarify the distinction between computational models and numerical methods, and to better understand the representational and the computational functions of models in simulations. (shrink)

A recent evolution of computer simulations has led to the emergence of complex computer simulations. In particular, the need to formalize composite objects (those objects that are composed of other objects) has led to what the author suggests calling pluriformalizations, i.e. formalizations that are based on distinct sub-models which are expressed in a variety of heterogeneous symbolic languages. With the help of four case-studies, he shows that such pluriformalizations enable to formalize distinctly but simultaneously either different aspects or different parts (...) or different scales of the same object or system. From an epistemological standpoint, he suggests that this kind of computer-aided complex formalization of composite objects renew the traditional relations between computer simulations, theoretical models and operational models. (shrink)

The notion of Simulative Reasoning in the study of propositional attitudes within Artificial Intelligence (AI) is strongly related to the Simulation Theory of mental ascription in Philosophy. Roughly speaking, when an AI system engages in Simulative Reasoning about a target agent, it reasons with that agent’s beliefs as temporary hypotheses of its own, thereby coming to conclusions about what the agent might conclude or might have concluded. The contrast is with non-simulative meta-reasoning, where the AI system reasons within a (...) detailed theory about the agent’s (conjectured) reasoning acts. The motive within AI for preferring Simulative Reasoning is that it is more convenient and efficient, because of a simplification of the representations and reasoning processes. The chapter discusses this advantage in detail. It also sketches the use of Simulative Reasoning in an AI natural language processing system, ATT-Meta, that is currently being implemented. This system is directed at the understanding of propositional attitude reports. In ATT-Meta, Simulative Reasoning is yoked to a somewhat independent set of ideas about how attitude reports should be treated. Central here are the claims that (a) speakers often employ commonsense (and largely metaphorical) models of mind in describing agents’ attitudes, (b) the listener accordingly needs often to reason within the terms of such models, rather than on the basis of any objectively justifiable characterization of the mind, and (c) the commonsense models filter the suggestions that Simulative Reasoning comes up with concerning target agents’ reasoning conclusions. There is a yet tighter connection between the commonsense models and the Simulative Reasoning. It turns out that Simulative Reasoning can be rationally reconstructed in terms of a more general type of reasoning about the possibly-counterfactual “world” that the target agent believes in, together with an assumption that that agent has a faithful representation of the world. In the ATT-Meta approach, the reasoner adopts that assumption when it views the target agent through a particular commonsense model (called IDEAS-AS-MODELS). (shrink)

I show that the Pinkerton rule in conspiracy law is doctrinally and morally flawed. Unlike past critics of the rule, I propose a statutory fix that preserves and reforms it rather than abolishing it entirely. As I will show, this accommodates authors like Neil Katyal who have defended the rule as an important crime fighting tool while also fixing most of the traditional problems with it identified by critics like Wayne LaFave. Pinkerton is a vicarious liability rule that makes conspirators (...) criminally responsible for the foreseeable crimes of their coconspirators committed in furtherance of the conspiracy. It has two big problems: (1) Doctrinally, it breaks the logic of the many state criminal codes that are based on the Model Penal Code. (2) Ethically, it infringes the culpability constraint on the criminal law by imposing excessive punishments on defendants who did not even consciously suspect that their coconspirators would commit additional crimes that were not the object of the conspiracy. These problems are most acute in Texas, where Pinkerton can be combined with capital murder charges to produce automatic life without parole sentences. The Texas example is an extreme illustration of the problem of unintended consequences when state legislators tinker with the carefully drafted, interlocking provisions of a model code. The new statute I propose would put the penal code back in order and respect the culpability constraint. In the latter aspect, it is informed by leading work in philosophical ethics on blameworthiness and culpability. (shrink)

According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, (...) in the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system. (shrink)

Mathematical models are a well established tool in most natural sciences. Although models have been neglected by the philosophy of science for a long time, their epistemological status as a link between theory and reality is now fairly well understood. However, regarding the epistemological status of mathematical models in the social sciences, there still exists a considerable unclarity. In my paper I argue that this results from specific challenges that mathematical models and especially computer simulations face in the social sciences. (...) The most important difference between the social sciences and the natural sciences with respect to modeling is that in the social sciences powerful and well confirmed background theories (like Newtonian mechanics, quantum mechanics or the theory of relativity in physics) do not exist in the social sciences. Therefore, an epistemology of models that is formed on the role model of physics may not be appropriate for the social sciences. I discuss the challenges that modeling faces in the social sciences and point out their epistemological consequences. The most important consequences are that greater emphasis must be placed on empirical validation than on theoretical validation and that the relevance of purely theoretical simulations is strongly limited. (shrink)

Nick Bostrom’s recently patched ‘‘simulation argument’’ (Bostrom in Philos Q 53:243–255, 2003; Bos- trom and Kulczycki in Analysis 71:54–61, 2011) purports to demonstrate the probability that we ‘‘live’’ now in an ‘‘ancestor simulation’’—that is as a simulation of a period prior to that in which a civilization more advanced than our own—‘‘post-human’’—becomes able to simulate such a state of affairs as ours. As such simulations under consid- eration resemble ‘‘brains in vats’’ (BIVs) and may appear open to (...) similar objections, the paper begins by reviewing objections to BIV-type proposals, specifically those due a presumed mad envatter. In counter example, we explore the motivating rationale behind current work in the development of psychologically realistic social simula- tions. Further concerns about rendering human cognition in a computational medium are confronted through review of current dynamic systems models of cognitive agency. In these models, aspects of the human condition are repro- duced that may in other forms be considered incomputable, i.e., political voice, predictive planning, and consciousness. The paper then argues that simulations afford a unique potential to secure a post-human future, and may be nec- essary for a pre-post-human civilization like our own to achieve and to maintain a post-human situation. Long-s- tanding philosophical interest in tools of this nature for Aristotle’s ‘‘statesman’’ and more recently for E.O. Wilson in the 1990s is observed. Self-extinction-level threats from State and individual levels of organization are compared, and a likely dependence on large-scale psychologically realistic simulations to get past self-extinction-level threats is projected. In the end, Bostrom’s basic argument for the conviction that we exist now in a simulation is reaffirmed. (shrink)

Previous simulation models have found positive effects of cognitive diversity on group performance, but have not explored effects of diversity in demographics (e.g., gender, ethnicity). In this paper, we present an agent-based model that captures two empirically supported hypotheses about how demographic diversity can improve group performance. The results of our simulations suggest that, even when social identities are not associated with distinctive task-related cognitive resources, demographic diversity can, in certain circumstances, benefit collective performance by counteracting two types (...) of conformity that can arise in homogeneous groups: those relating to group-based trust and those connected to normative expectations towards in-groups. (shrink)

In an attempt to determine the epistemic status of computer simulation results, philosophers of science have recently explored the similarities and differences between computer simulations and experiments. One question that arises is whether and, if so, when, simulation results constitute novel empirical data. It is often supposed that computer simulation results could never be empirical or novel because simulations never interact with their targets, and cannot go beyond their programming. This paper argues against this position by examining (...) whether, and under what conditions, the features of empiricality and novelty could be displayed by computer simulation data. I show that, to the extent that certain familiar measurement results have these features, so can some computer simulation results. (shrink)

Ensemble perception—the encoding of objects by their group properties—is known to be resistant to outlier noise. However, this resistance is somewhat paradoxical: how can the visual system determine which stimuli are outliers without already having derived statistical properties of the ensemble? A simple solution would be that ensemble perception is not a simple, one-step process; instead, outliers are detected through iterative computations that identify items with high deviance from the mean and reduce their weight in the representation over time. (...) Here we tested this hypothesis. In Experiment 1, we found evidence that outliers are discounted from mean orientation judgments, extending previous results from ensemble face perception. In Experiment 2, we tested the timing of outlier rejection by having participants perform speeded judgments of sets with or without outliers. We observed significant increases in reaction time (RT) when outliers were present, but a decrease compared to no-outlier sets of matched range suggesting that range alone did not drive RTs. In Experiment 3 we tested the timing by which outlier noise reduces over time. We presented sets for variable exposure durations and found that noise decreases linearly over time. Altogether these results suggest that ensemble representations are optimized through iterative computations aimed at reducing noise. The finding that ensemble perception is an iterative process provides a useful framework for understanding contextual effects on ensemble perception. (shrink)

‘The problem with simulations is that they are doomed to succeed.’ So runs a common criticism of simulations—that they can be used to ‘prove’ anything and are thus of little or no scientific value. While this particular objection represents a minority view, especially among those who work with simulations in a scientific context, it raises a difficult question: what standards should we use to differentiate a simulation that fails from one that succeeds? In this paper we build on a (...) structural analysis of simulation developed in previous work to provide an evaluative account of the variety of ways in which simulations do fail. We expand the structural analysis in terms of the relationship between a simulation and its real-world target emphasizing the important role of aspects intended to correspond and also those specifically intended not to correspond to reality. The result is an outline both of the ways in which simulations can fail and the scientific importance of those various forms of failure. (shrink)

(Draft of Feb 2023, see upcoming issue for Chalmers' reply) In Reality+: Virtual Worlds and the Problems of Philosophy, David Chalmers argues, among other things, that: if we are living in a full-scale simulation, we would still enjoy broad swathes of knowledge about non-psychological entities, such as atoms and shrubs; and, our lives might still be deeply meaningful. Chalmers views these claims as at least weakly connected: The former claim helps forestall a concern that if objects in the (...) class='Hi'>simulation are not genuine (and so not knowable), then life in the simulation is illusory and therefore, not as valuable as a non-simulated life. Taking up these questions, I argue that in general, the value of social knowledge for a meaningful life dramatically swamps the value of non-social knowledge for a meaningful life. Along the way, I propose a non-additive model of the meaningfulness of life, according to which the overall effect of some potential contributor of value to a life depends in part on what is already in a life. One upshot is that the vindication of non-social knowledge, absent a correlative vindication of social knowledge, contributes either not at all or scarcely at all to the claim that our lives in the simulation might be deeply meaningful. This is so even though the vindication of non-social knowledge does forestall the concern that in the simulation, our lives might be wholly meaningless. (shrink)

This chapter focuses on a novel class of models used in frontier research in the bioengineering sciences – in vitro simulation models – that provide the basis for biological experimentation. These bioengineered models are hybrid constructions, composed of living tissues or cells and engineered materials. Specifically, it discusses the processes through which in vitro models were built, experimented with, and justified in a tissue engineering lab. It examines processes of design, construction, experimentation, evaluation, and redesign of in vitro (...) class='Hi'>simulation models, in general, as instances of building the source analogy (as distinguished from retrieving an analogy), which figures prominently in creative frontier scientific research. Building the analogical source is a bootstrapping process, which furthers the articulation, as well as the solution of the problem. -/- . (shrink)

It is sometimes said that simulation can serve as epistemic substitute for experimentation. Such a claim might be suggested by the fast-spreading use of computer simulation to investigate phenomena not accessible to experimentation (in astrophysics, ecology, economics, climatology, etc.). But what does that mean? The paper starts with a clarification of the terms of the issue and then focuses on two powerful arguments for the view that simulation and experimentation are ‘epistemically on a par’. One is based (...) on the claim that, in experimentation, no less than in simulation, it is not the system under study that is manipulated but a system that ‘stands-in’ for it. The other one highlights the pervasive use of models in experimentation. It will be argued that these arguments, as compelling as they might seem, are each based on a mistaken interpretation of experimentation and that, far from simulation and experimentation being epistemically on a par, they do not have the same epistemic function, do not produce the same kind of epistemic results. (shrink)

This article aims to develop a new account of scientific explanation for computer simulations. To this end, two questions are answered: what is the explanatory relation for computer simulations? And what kind of epistemic gain should be expected? For several reasons tailored to the benefits and needs of computer simulations, these questions are better answered within the unificationist model of scientific explanation. Unlike previous efforts in the literature, I submit that the explanatory relation is between the simulation (...) class='Hi'>model and the results of the simulation. I also argue that our epistemic gain goes beyond the unificationist account, encompassing a practical dimension as well. (shrink)

Dans un nombre croissant de domaines scientifiques - sciences de la nature, sciences humaines aussi bien que sciences des artefacts -, la simulation ne joue plus le rôle de succédané temporaire d'une théorie encore en gésine parce que non encore élaborée ; c'est-à-dire qu'elle ne joue plus systématiquement le rôle d'un modèle provisoire ou d'un schéma servant à condenser les mesures. C'est qu'elle n'a pas la nature d'un signe graphique, linguistique ou mathématique. Elle joue au contraire de plus en (...) plus le rôle d'une réplication détaillée du réel : elle est une intuition reconstruite avec justesse mais sans abstraction rationnelle et généralisante, donc sans transfiguration iconique. Une des limites de l'épistémologie dialectique de Bachelard tient à ce qu'elle ne donne pas les concepts pour penser assez distinctement ces pratiques contemporaines de simulation. C'est pourquoi l'A. propose de concevoir l'idée que la science contemporaine se développe non plus selon la seule dialectique matérialisme / rationalisme, mais selon la triade rationalisme/computationalisme/matérialisme. (shrink)

Since the 1990’s, social sciences are living their computational turn. This paper aims to clarify the epistemological meaning of this turn. To do this, we have to discriminate between different epistemic functions of computation among the diverse uses of computers for modeling and simulating in the social sciences. Because of the introduction of a new – and often more user-friendly – way of formalizing and computing, the question of realism of formalisms and of proof value of computational treatments reemerges. Facing (...) the spreading of computational simulations in all disciplines, some enthusiastic observers are claiming that we are entering a new era of unity for social sciences. Finally, the article shows that the conceptual and epistemological distinctions presented in the first sections lead to a more mitigated position: the transdisciplinary computational turn is a great one, but it is of a methodological nature. (shrink)

Outlined here is a simulation hypothesis approach that uses an expanding (the simulation clock-rate measured in units of Planck time) 4-axis hyper-sphere and mathematical particles that oscillate between an electric wave-state and a mass (unit of Planck mass per unit of Planck time) point-state. Particles are assigned a spin axis which determines the direction in which they are pulled by this (hyper-sphere pilot wave) expansion, thus all particles travel at, and only at, the velocity of expansion (the origin (...) of $c$), however only the particle point-state has definable co-ordinates within the hyper-sphere. Photons are the mechanism of information exchange, as they lack a mass state they can only travel laterally (in hypersphere co-ordinate terms) between particles and so this hypersphere expansion cannot be directly observed, relativity then becomes the mathematics of perspective translating between the absolute (hypersphere) and the relative motion (3D space) co-ordinate systems. A discrete `pixel' lattice geometry is assigned as the gravitational space. Units of $\hbar c$ `physically' link particles into orbital pairs. As these are direct particle to particle links, a gravitational force between macro objects is not required, the gravitational orbit as the sum of these individual orbiting pairs. A 14.6 billion year old hyper-sphere (the sum of Planck black-hole units) has similar parameters to the cosmic microwave background. The Casimir force is a measure of the background radiation density. (shrink)

Together, the code and inferential models of communication are often thought to range over all cases of communication. However, their prevailing versions seem unable to fully explain what I call underdeterminacy without ostension. The latter is constituted by communication where stimuli that are not (nor appear to be) produced with communicative or informative intentions nevertheless communicate information underdetermined by the relevant codes. Though the prevailing accounts of communication cannot fully explain how communication works in such cases, I suggest that some (...) version of the inferential model can—if we allow it to extend to non‐ostensive, non‐intentional behaviors. (shrink)

The formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences. Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain models are sufficient to generate emergent macrostructures of interest. The description of scientific practice implies additional epistemic conceptions of scientific knowledge. Three kinds of knowledge that account for a comprehensive description of the discipline were identified: formal, empirical and intentional knowledge. The use (...) of formal conceptions of computation for describing simulation is refuted; the roles of programming languages according to intentional accounts of computation are identified; and the roles of iconographic programming languages and aesthetic machines in simulation are characterized. The roles that simulation and intentional decision making may be able to play in a participative information society are also discussed. (shrink)

The goal of the article is to explore what is the most probable type of simulation in which humanity lives (if any) and how this affects simulation termination risks. We firstly explore the question of what kind of simulation in which humanity is most likely located based on pure theoretical reasoning. We suggest a new patch to the classical simulation argument, showing that we are likely simulated not by our own descendants, but by alien civilizations. Based (...) on this, we provide classification of different possible simulations and we find that simpler, less expensive and one-person-centered simulations, resurrectional simulations, or simulations of the first artificial general intelligence’s (AGI’s) origin (singularity simulations) should dominate. Also, simulations which simulate the 21st century and global catastrophic risks are probable. We then explore whether the simulation could collapse or be terminated. Most simulations must be terminated after they model the singularity or after they model a global catastrophe before the singularity. Undeniably observed glitches, but not philosophical speculations could result in simulation termination. The simulation could collapse if it is overwhelmed by glitches. The Doomsday Argument in simulations implies termination soon. We conclude that all types of the most probable simulations except resurrectional simulations are prone to termination risks in a relatively short time frame of hundreds of years or less from now. (shrink)

Why are natural theories pre-well-ordered by consistency strength? In previous work, an approach to this question was proposed. This approach was inspired by Martin's Conjecture, one of the most prominent conjectures in recursion theory. Fixing a reasonable subsystem $T$ of arithmetic, the goal was to classify the recursive functions that are monotone with respect to the Lindenbaum algebra of $T$. According to an optimistic conjecture, roughly, every such function must be equivalent to an iterate $\mathsf{Con}_T^\alpha$ of the consistency operator ``in (...) the limit'' within the ultrafilter of sentences that are true in the standard model. In previous work the author established the first case of this optimistic conjecture; roughly, every recursive monotone function is either as weak as the identity operator in the limit or as strong as $\mathsf{Con}_T$ in the limit. Yet in this note we prove that this optimistic conjecture fails already at the next step; there are recursive monotone functions that are neither as weak as $\mathsf{Con}_T$ in the limit nor as strong as $\mathsf{Con}_T^2$ in the limit. In fact, for every $\alpha$, we produce a function that is cofinally equivalent to $\mathsf{Con}^\alpha_T$ yet cofinally equivalent to $\mathsf{Con}_T$. (shrink)

The theory of mind debate has reached a “hybrid consensus” concerning the status of theory-theory and simulation-theory. Extant hybrid models either specify co-dependency and implementation relations, or distribute mentalizing tasks according to folk-psychological categories. By relying on a non-developmental framework these models fail to capture the central connection between simulation and theory. I propose a “dynamic” hybrid that is informed by recent work on the nature of similarity cognition. I claim that Gentner’s model of structure-mapping allows us (...) to understand simulation as a process in which psychological representations are aligned, causing the spontaneous abstraction of theoretical generalizations about the psychological domain. (shrink)

The notion of empathy has been explicated in different ways in the current debate on how to understand others. Whereas defenders of simulation-based approaches claim that empathy involves some kind of isomorphism between the empathizer’s and the target’s mental state, defenders of the phenomenological account vehemently deny this and claim that empathy allows us to directly perceive someone else’s mental states. Although these views are typically presented as being opposed, I argue that at least one version of a (...) class='Hi'>simulation-based approach—the account given by de Vignemont and Jacob—is compatible with the direct-perception view. My argument has two parts: My first step is to show that the conflict between these accounts is not—as it seems at first glance—a disagreement on the mechanism by which empathy comes about. Rather, it is due to the fact that their proponents attribute two very different roles to empathy in understanding others. My second step is to introduce Stein’s account of empathy. By not restricting empathy to either one of these two roles, her process model of empathy helps to see how the divergent intuitions that have been brought forward in the current debate could be integrated. (shrink)

This article compares three models for conceptualizing the political and ethical challenges of contemporary genetics, genomics, and postgenomics. The three analytical approaches are referred to as the state-politics model, the biopolitical model, and the infopolitical model. Each of these models is valuable for different purposes. But comparing these models in terms of their influence in contemporary discussions, the first is by far the dominant approach, the second is gaining in importance, and the third is almost entirely neglected. (...) The widespread neglect of the infopolitical dimensions of genetic sciences focused by the third model is puzzling in light of the fact that genetics, genomics, and postgenomics are all pre-eminent information sciences. The infopolitical model thus aims to bring into clearer view the specific political and ethical problems engendered by this informational nature of the genetic sciences. This model offers a way of understanding how ethically-salient and politically-fraught conceptual assumptions can be embedded in informational architectures such as algorithms and the formats (or data structures) upon which they rely. (shrink)

According to the iterative conception of set, sets are formed in stages. According to the purely iterative conception of set, sets are formed by iterated application of a set-of operation. The cumulative hierarchy is a mathematical realization of the iterative conception of set. A mathematical realization of the purely iterative conception can be found in Peter Aczel’s type-theoretic model of constructive set theory. I will explain Aczel’s model construction in a way that presupposes no (...) previous familiarity with the theories on which it is based. (shrink)