Psychopathy is increasingly in the public eye. However, it is yet to be fully and effectively understood. Within the context of the DSM-IV, for example, it is best regarded as a complex family of disorders. The upside is that this family can be tightly related along common dimensions. Characteristic marks of psychopaths include a lack of guilt and remorse for paradigm case immoral actions, leading to the common conception of psychopathy rooted in affective dysfunctions. An adequate portrait of psychopathy is (...) much more complicated, however. Though some neural regions and corresponding functions are commonly indicated, they range across those responsible for action planning and learning, as well as emotional processes. Accordingly, a complete fine-grained map of all neural mechanisms responsible for psychopathy has not been realized, and even if it were, such a map would have limited utility outside of the context of surgical or chemical intervention. The utility of a neural-level understanding of psychopathy is further limited by the fact that it is only applicable in the clinical identification of individual subjects, and the neuro-chemical/biological correction of those subjects after they are positively identified as psychopaths. On the other hand, an information processing model of moral cognition provides for wider-ranging applications. The theoretical and practical implications for such a feasible working model of psychopathic personalities are assessed. Finally, this chapter raises the possibility of directed modification of social-environmental factors discouraging the development of psychopathic personalities in the first place, modifications which are also open to simulation and testing in terms of the same model of moral cognition. (shrink)

How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting stimulus regularities (...) on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes. (shrink)

This chapter explores to what extent some core ideas of predictive processing can be applied to the phenomenology of time consciousness. The focus is on the experienced continuity of consciously perceived, temporally extended phenomena (such as enduring processes and successions of events). The main claim is that the hierarchy of representations posited by hierarchical predictive processing models can contribute to a deepened understanding of the continuity of consciousness. Computationally, such models show that sequences of events can be represented as states (...) of a hierarchy of dynamical systems. Phenomenologically, they suggest a more fine-grained analysis of the perceptual contents of the specious present, in terms of a hierarchy of temporal wholes. Visual perception of static scenes not only contains perceived objects and regions but also spatial gist; similarly, auditory perception of temporal sequences, such as melodies, involves not only perceiving individual notes but also slightly more abstract features (temporal gist), which have longer temporal durations (e.g., emotional character or rhythm). Further investigations into these elusive contents of conscious perception may be facilitated by findings regarding its neural underpinnings. Predictive processing models suggest that sensorimotor areas may influence these contents. (shrink)

Models of discourse and narration elaborated within the classical compositional framework have been characterized as bottom-up models, according to which discourse analysis proceeds incrementally, from phrase and sentence local meaning to discourse global meaning. In this paper we will argue against these models. Assuming as a case study the issue of discourse coherence, we suggest that the assessment of coherence is a top-down process, in which the construction of a situational interpretation at the global meaning level guides local meaning (...) analysis. In support of our hypothesis, we explore the role of executive functions (brain functions involved in planning and organization of goal-oriented behaviors) in coherence’s establishment, discussing the results of several studies on narrative abilities of patients with brain injuries. We suggest that, compared to other models of discourse processing focused on comprehension, our model is a viable candidate for an integrated account of discourse comprehension and production. (shrink)

The purpose of this paper is to show that the Elementary Process Theory (EPT) agrees with the knowledge of the physical world obtained from the successful predictions of Special Relativity (SR). For that matter, a recently developed method is applied: a categorical model of the EPT that incorporates SR is fully specified. Ultimate constituents of the universe of the EPT are modeled as point-particles, gamma-rays, or time-like strings, all represented by integrable hyperreal functions on Minkowski space. This proves (...) that the EPT agrees with SR. -/- Edit: this preprint differs significantly from the published chapter. (shrink)

Written in broad strokes, this paper attempts to draw form Krishnamurti’s life and teachings, a hermeneutics of the human soul’s quest-journey towards transcendent wholeness. It begins with an attempt to frame K’s “process” (the name given to the painful ordeals in his youth that many believe were the catalyst responsible for his metamorphosis) through a variety of disciplines and cultural perspectives, some of which underscore the impasse of scientific objectivity and the limits of phenomenalist categories in general. It then (...) explores the procedures and conceits of present technologies of self-transformation via pseudomeditative body work and suggests that this subject can only be confirmed by an experience so intimately and subversively (to its own object) subjective that it risks undermining its own legitimacy in the face of our body-phobic Cartesian cultural ethos that holds sacrosanct the mind-body split. -/- It then explores the deeper origins and history of this problem from the pre-Socratics to the misconceptions of modern mathematics about the proper place of metaphor and paradox and underscores how present day false consciousness fails to discriminate between a “noumenal” world and its conditioned “phenomenal” counterfeit copy. It ends with a brief meditation on K’s process. (shrink)

De Neys (2021) argues that the debate between single- and dual-process theorists of thought has become both empirically intractable and scientifically inconsequential. I argue that this is true only under the traditional framing of the debate—when single- and dual-process theories are understood as claims about whether thought processes share the same defining properties (e.g., making mathematical judgments) or have two different defining properties (e.g., making mathematical judgments autonomously versus via access to a central working memory capacity), respectively. But (...) if single- and dual-process theories are understood in cognitive modeling terms as claims about whether thought processes function to implement one or two broad types of algorithms, respectively, then the debate becomes scientifically consequential and, presumably, empirically tractable. So, I argue, the correct response to the current state of the debate is not to abandon it, as De Neys suggests, but to reframe it as a debate about cognitive models. (shrink)

This paper argues that scientific studies distinguish themselves from other studies by a combination of their processes, their (knowledge) elements and the roles of these elements. This is supported by constructing a process model. An illustrative example based on Newtonian mechanics shows how scientific knowledge is structured according to the process model. To distinguish scientific studies from research and scientific research, two additional process models are built for such processes. We apply these process models: (...) (1) to argue that scientific progress should emphasize both the process of change and the content of change; (2) to chart the major stages of scientific study development; and (3) to define “science”. (shrink)

Human cognitive process as a combination of the triad Knower - Knowing - Known and the language learning process as a combination of the triad Subject -Verb - Object will be understood in the light of ancient Indian wisdom as revealed in the Upanishads and will be presented. -/- A physics awareness of Advaita (No Two) concept will be used to model human mental processes such as – Knowing / Learning, Perception / Thinking / Logic, Understanding / (...) Experiencing / Awareness of meaning of a sentence. This awareness will further be used to prepare a flow-chart / block-diagram involving gross energy -transformations in human cognitive process. -/- This awareness will be corresponded to the awareness of Sri Aurobindo and Sri Ramana Maharshi on human consciousness. Implications of this model to natural language comprehension field of artificial intelligence will be presented combining with the ideas of connectionism. -/- . (shrink)

Sometimes we learn through the use of imagination. The epistemology of imagination asks how this is possible. One barrier to progress on this question has been a lack of agreement on how to characterize imagination; for example, is imagination a mental state, ability, character trait, or cognitive process? This paper argues that we should characterize imagination as a cognitive ability, exercises of which are cognitive processes. Following dual process theories of cognition developed in cognitive science, the set of (...) imaginative processes is then divided into two kinds: one that is unconscious, uncontrolled, and effortless, and another that is conscious, controlled, and effortful. This paper outlines the different epistemological strengths and weaknesses of the two kinds of imaginative process, and argues that a dual process model of imagination helpfully resolves or clarifies issues in the epistemology of imagination and the closely related epistemology of thought experiments. (shrink)

The exploration of the literature indicated that much studies abound in related areas. Much seems yet to be known about the nature of the relationship that exists between managerial variables and the sustainability of graduate programmes. To bridge this gap, we utilized a standardised multiple regression approach to build up linear models that examine three managerial processes (strategic planning, staff and information/communication management) and how they affect three proxies of the sustainability of graduate programmes (availability of funds and facilities, as (...) well as supervision) respectively and cumulatively. Quantitative data were obtained from an entire population of 149 managers (Head of Departments and Deans) in the University of Calabar, Calabar, Nigeria using a questionnaire. Findings emerged, among others, a significant relationship between each of the managerial processes to the sustainability of graduate programmes generally and particularly in terms of availability of funds, facilities and supervision; the three predictor variables partially and jointly accounted for significant proportions in the sustainability of graduate programmes generally and specifically in terms of the various dimensions. Based on this evidence, one general and three partial predictive linear equations, as well as models were derived, while relevant action-based implications for effective management and practice were discussed. (shrink)

Item analysis is a general term that refers to the specific methods used in education to evaluate test items, typically for the purpose of test construction and revision. Construction and analysis of science examinations in high school curricula needs the integration of integrated process and skill type which help students develop their rational and logical thinking. This exploratory study aimed to investigate the comparative results of item analyses using Rasch Model Analysis and SPSS. It examined the reliability, mean (...) difficulty, mean ability, discrimination index, mean trend scores, infit and misfit, and item-person and fit maps using the results of the Basic & Integrated Science Process and Skill Test (BISPST) administered to secondary science high school teachers in the Division of Nueva Vizcaya. The Rasch Model Analysis and SPSS revealed the same unsatisfactory value of internal consistency or the reliability coefficient Cronbach’s alpha (0.66 and 0.67), mean score (19.52) and standard deviation (4.53) of the BISPST. The mean item difficulty was set at 0 by definition (SD = 2.02) and the mean examinee ability was 1.56 (SD = 0.98), which means that the examinees were able to correctly answer 61% of items on average. 33 items with difficulty lower than the least able examinee. The mean ability using Rasch Model Analysis per item showed that high performers in the test got the correct answers compared to the low performing group. This is the same and consistent with the results of the mean trend scores of the upper, middle and lower groups as generated by the SPSS. Choices in the BISPST were found to be effective distracters. Although most items needs revision as revealed by the values generated by both softwares, no items were found to be misfit in the distribution. (shrink)

Predictive processing models of perception take issue with standard models of perception as hierarchical bottom-up processing modulated by memory and attention. The predictive framework posits that the brain generates predictions about stimuli, which are matched to the incoming signal. Mismatches between predictions and the incoming signal – so-called prediction errors – are then used to generate new and better predictions until the prediction errors have been minimized, at which point a perception arises. Predictive models hold that all bottom-up processes are (...) signals conveying prediction errors to higher areas, which respond by updating their predictions. We take issue with this claim and argue that object recognition requires bottom-up processing that cannot be understood in terms of prediction errors. Along the way, we expand on previous work casting doubt on the framework's ability to account for attention. Specifically, we argue that the type of attention that allows us to rapidly extract the gist of an object or scene presents an additional challenge to the predictive approach. We conclude by considering how the framework may be augmented to avoid these problems. (shrink)

In the last two decades, software process modeling has been an area of interest within both academia and industry. Software process modeling aims at defining and representing software processes in the form of models. A software process model represents the medium that allows better understanding, management and control of the software process. Software process metamodeling rather, provides standard metamodels which enable the defining of customized software process models for a specific project in hand (...) by instantiation. Several software process modeling/meta-modeling languages have been introduced to formalize software process models. Nonetheless, none of them has managed to introduce a compatible yet precise language to include all necessary concepts and information for software process modeling. This paper presents Software Process Meta-Modeling and Notation (SP2MN); a meta-modeling language that provides simple and expressive graphical notations for the aim of software process modeling. SP2MN has been evaluated based upon the well-known ISPW-6 process example, a standard benchmark problem for software process modeling. SP2MN has proved that it presents a valid and expressive software process modeling language. (shrink)

Currently there are at least four sizeable projects going on to establish the gravitational acceleration of massive antiparticles on earth. While general relativity and modern quantum theories strictly forbid any repulsive gravity, it has not yet been established experimentally that gravity is attraction only. With that in mind, the Elementary Process Theory (EPT) is a rather abstract theory that has been developed from the hypothesis that massive antiparticles are repulsed by the gravitational field of a body of ordinary matter: (...) the EPT essentially describes the elementary processes by which the smallest massive systems have to interact with their environments for repulsive gravity to exist. In this paper we model a nonrelativistic, one-component massive system that evolves in time by the processes as described by the EPT in an environment described by classical fields: the main result is a semi-classical model of a process at Planck scale by which a non-relativistic onecomponent system interacts with its environment, such that the interaction has both gravitational and electromagnetic aspects. Some worked-out examples are provided, among which the repulsion of an antineutron by the gravitational field of the earth. The general conclusion is that the semi-classical model of the EPT corresponds to non-relativistic classical mechanics. Further research is aimed at demonstrating that the EPT has a model that reproduces the successful predictions of general relativity. (shrink)

Many biological processes and objects can be described by fractals. The paper uses a new type of objects – blinking fractals – that are not covered by traditional theories considering dynamics of self-similarity processes. It is shown that both traditional and blinking fractals can be successfully studied by a recent approach allowing one to work numerically with infinite and infinitesimal numbers. It is shown that blinking fractals can be applied for modeling complex processes of growth of biological systems including their (...) season changes. The new approach allows one to give various quantitative characteristics of the obtained blinking fractals models of biological systems. (shrink)

A widely debated issue in contemporary metaphysics is whether the modal profile of ordinary objects has to be explained in non-modal terms (that is, Thesis 1). However, how to solve such an issue with respect to occurrences – namely, processes and events – is a question that has been largely neglected in the current metaphysical debate. The general goal of this article is to start filling this gap. As a first result of the article, we make it plausible that, if (...) Thesis 1 holds for objects, then it also holds for processes and events. Then, we develop a metaphysical account of processes derived from Fine’s (1999, 2022) suggestions, according to which a process is a variable embodiment that is manifested by different events at the different times it goes on – namely, Thesis 2. We raised the challenge from the completion of a process that asks the Finean account of processes to explain relevant modal features of processes in non-modal terms. As a second result, we argue that four initially plausible strategies for solving such a challenge fall short of solving it. As a third result, we show that the theory of variable embodiments Fine formulates for objects must differ from the theory of variable embodiments that aims to model processes. We conclude by investigating some revisions to a theory of variable embodiments that aims to model processes. (shrink)

In this note, we consider a Merton model for default risk, where the firm’s value is driven by a Brownian motion and a compound Poisson process.

Bayesian models of legal arguments generally aim to produce a single integrated model, combining each of the legal arguments under consideration. This combined approach implicitly assumes that variables and their relationships can be represented without any contradiction or misalignment, and in a way that makes sense with respect to the competing argument narratives. This paper describes a novel approach to compare and ‘average’ Bayesian models of legal arguments that have been built independently and with no attempt to make them (...) consistent in terms of variables, causal assumptions or parameterization. The approach involves assessing whether competing models of legal arguments are explained or predict facts uncovered before or during the trial process. Those models that are more heavily disconfirmed by the facts are given lower weight, as model plausibility measures, in the Bayesian model comparison and averaging framework adopted. In this way a plurality of arguments is allowed yet a single judgement based on all arguments is possible and rational. (shrink)

We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides insight into the (...) common but little-discussed practices of iteratively reusing and repurposing data, which result in many datasets’ having a phylogeny—an origin and complex evolutionary history—that is relevant to their evaluation and future use. We relate these insights to the open-data and data-rescue movements, and highlight several future avenues of research that build on the PR view of data. (shrink)

Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and action control comprising levels (...) of generative models. I argue that this view is not entailed by a general Bayesian/predictive processing outlook. Bayesian approaches are compatible with distinct formats of mental representation. Focusing on Bayesian approaches to motor control, I argue that the junctures between different types of mental representation are places where the transitivity of hierarchical prediction may be broken, and I consider the upshot of this conclusion for broader discussions of cognitive architecture. (shrink)

Predictive processing theories are increasingly popular in philosophy of mind; such process theories often gain support from the Free Energy Principle (FEP)—a nor- mative principle for adaptive self-organized systems. Yet there is a current and much discussed debate about conflicting philosophical interpretations of FEP, e.g., repre- sentational versus non-representational. Here we argue that these different interpre- tations depend on implicit assumptions about what qualifies (or fails to qualify) as representational. We deploy the Free Energy Principle (FEP) instrumentally to dis- (...) tinguish four main notions of representation, which focus on organizational, struc- tural, content-related and functional aspects, respectively. The various ways that these different aspects matter in arriving at representational or non-representational interpretations of the Free Energy Principle are discussed. We also discuss how the Free Energy Principle may be seen as a unified view where terms that tradition- ally belong to different ontologies—e.g., notions of model and expectation versus notions of autopoiesis and synchronization—can be harmonized. However, rather than attempting to settle the representationalist versus non-representationalist debate and reveal something about what representations are simpliciter, this paper demon- strates how the Free Energy Principle may be used to reveal something about those partaking in the debate; namely, what our hidden assumptions about what represen- tations are—assumptions that act as sometimes antithetical starting points in this persistent philosophical debate. (shrink)

Borrowing the functional modeling approach common in systems and software engineering, an implementable model of the functions of human consciousness proposed to have the capacity for general problem solving ability transferable to any domain, or true self-aware intelligence, is presented. Being a functional model that is independent of implementation, this model is proposed to also be applicable to artificial consciousness, and to platforms that organize individuals into what is defined here as a first order collective consciousness, or (...) at higher orders into what is defined here as Nth order collective consciousness. Part I of this two-part article includes: Summary; Introduction; Set of Postulates One; Set of Postulates Two; Overview of the Model; Model of Homeostasis; Model of the Functional Units; Model of the Body System; Model of the Other Basic Life Processes; Model of the Other Functional Systems; Model of Perceptions in the Perceptual Fields; Model of Body Processes as Paths in the Perceptual Field; & Model of Conscious Awareness. (shrink)

Recent work in cognitive modelling has found that most of the data that has been cited as evidence for the dual-process theory (DPT) of reasoning is best explained by non-linear, “monotonic” one-process models (Stephens et al., 2018, 2019). In this paper, I consider an important caveat of this research: it uses models that are committed to unrealistic assumptions about how effectively task conditions can isolate Type-1 and Type-2 reasoning. To avoid this caveat, I develop a coordinated theoretical, experimental, (...) and modelling strategy to better test DPT. First, I propose that Type-1 and Type-2 reasoning are defined as reasoning that precedes and follows metacognitive control, respectively. Second, I argue that reasoning that precedes and follows metacognitive control can be effectively isolated using debiasing paradigms that manipulate metacognitive heuristics (e.g., processing fluency) to prevent or trigger metacognitive control, respectively. Third, I argue that monotonic modelling can allow us to decisively test DPT only when we use them to analyse data from this particular kind of debiasing paradigm. (shrink)

In this topical section, we highlight the next step of research on modeling aiming to contribute to the emerging literature that radically refrains from approaching modeling as a scientific endeavor. Modeling surpasses “doing science” because it is frequently incorporated into decision-making processes in politics and management, i.e., areas which are not solely epistemically oriented. We do not refer to the production of models in academia for abstract or imaginary applications in practical fields, but instead highlight the real entwinement of science (...) and policy and the real erosion of their boundaries. Models in decision making – due to their strong entwinement with policy and management – are utilized differently than models in science; they are employed for different purposes and with different constraints. We claim that “being a part of decision-making” implies that models are elements of a very particular situation, in which knowledge about the present and the future is limited but dependence of decisions on the future is distinct. Emphasis on the future indicates that decisions are made about actions that have severe and lasting consequences. In these specific situations, models enable not only the acquisition of knowledge (the primary goal of science) but also enable deciding upon actions that change the course of events. As a result, there are specific ways to construct effective models and justify their results. Although some studies have explored this topic, our understanding of how models contribute to decision making outside of science remains fragmentary. This topical section aims to fill this gap in research and formulate an agenda for additional and more systematic investigations in the field. (shrink)

This study aims to use the Asian knowledge model “APO” as a determinant for performance excellence in universities and identifying the most effecting factors on it. This study was applied on Al-Azhar University in Gaza strip. The result of the study showed that (APO) model is valid as a measure and there are four dimensions in the model affecting significantly more than the others (university processes, KM leadership, personnel, KM outputs). Furthermore, performance excellence produced though modernizing the (...) means of education, curriculum development, technology and flexibility in the organizational structure. The study recommends expanding the usage of (APO) model, enhancing the role of knowledge leadership, technology, organizational flexibility, sharing culture and incentive systems that encouraging innovation. (shrink)

Existing studies of the multi-group dynamics of prejudiced societies focus on the social- psychological knowledge behind the relevant processes. We instead create a multi-agent framework that simulates the propagation of prejudice and measures its tangible impact on prosperity. Levels of prosperity are tracked for individuals as well as larger social structures including groups and factions. We model social interactions using the Continuous Prisoner's Dilemma (CPD) and a new agent type called a prejudiced agent. Our simulations show that even modeling (...) prejudice as an exclusively out-group phenomenon nonetheless generates implicit in-group promotion, leading to higher relative prosperity of a prejudiced population. This skew in prosperity is seen to be correlated to factors such as size difference between groups, and the fraction of prejudiced agents in a group. Our model is a step towards a deeper understanding of the origins, propagation, and ramifications of prejudice through simulative studies grounded in apt theoretical backgrounds. (shrink)

Cognitive agents, whether human or computer, that engage in natural-language discourse and that have beliefs about the beliefs of other cognitive agents must be able to represent objects the way they believe them to be and the way they believe others believe them to be. They must be able to represent other cognitive agents both as objects of beliefs and as agents of beliefs. They must be able to represent their own beliefs, and they must be able to represent beliefs (...) as objects of beliefs. These requirements raise questions about the number of tokens of the belief representation language needed to represent believers and propositions in their normal roles and in their roles as objects of beliefs. In this paper, we explicate the relations among nodes, mental tokens, concepts, actual objects, concepts in the belief spaces of an agent and the agent's model of other agents, concepts of other cognitive agents, and propositions. We extend, deepen, and clarify our theory of intensional knowledge representation for natural-language processing, as presented in previous papers and in light of objections raised by others. The essential claim is that tokens in a knowledge-representation system represent only intensions and not extensions. We are pursuing this investigation by building CASSIE, a computer model of a cognitive agent and, to the extent she works, a cognitive agent herself. CASSIE's mind is implemented in the SNePS knowledge-representation and reasoning system. (shrink)

In what follows I propose to bring out certain methodological properties of projects of modelling the tacit realm that bear on the kinds of modelling done in connection with scientific cognition by computer as well as by ethnomethodological sociologists, both of whom must make some claims about the tacit in the course of their efforts to model cognition. The same issues, I will suggest, bear on the project of a cognitive psychology of science as well.

In this paper, I present a conception of meaning in natural language that I call the ‘process model’. According to this conception, meaning must be regarded as the result of a process of interaction in a community of cognitive-linguistic agents, with one another and with the environment. Drawing on this understanding, I argue that the study of meaning should no longer focus on logical analysis, but rather on an empirical perspective similar to the one in the other (...) social sciences. I briefly compare this view with semantic Platonism, as well as with Wittgenstein’s and Quine’s approaches to meaning. Finally, I outline a way in which this approach could be applied to two current problems in the philosophy of language: the treatment of linguistic vagueness and the definition of truth. The treatment of all these questions is very cursory, as a sort of travel guide for a future more detailed research. (shrink)

[This is an edited version of a keynote talk at the conference on Neural Information Processing Systems (NeurIPS) on November 28, 2022, with some minor additions and subtractions.] -/- There has recently been widespread discussion of whether large language models might be sentient or conscious. Should we take this idea seriously? I will break down the strongest reasons for and against. Given mainstream assumptions in the science of consciousness, there are significant obstacles to consciousness in current models: for example, their (...) lack of recurrent processing, a global workspace, and unified agency. At the same time, it is quite possible that these obstacles will be overcome in the next decade or so. I conclude that while it is somewhat unlikely that current large language models are conscious, we should take seriously the possibility that successors to large language models may be conscious in the not-too-distant future. (shrink)

The work of Gregory Bateson offers a metaphysical basis for a “process psychology,” that is, a view of psychological practice and research guided by an ontology of becoming—identifying change, difference, and relationship as the basic elements of a foundational metaphysics. This article explores the relevance of Bateson's recursive epistemology, his re-conception of the Great Chain of Being, a first-principles approach to defining the nature of mind, and understandings of interaction and difference, pattern and symmetry, interpretation and context. Bateson's philosophical (...) contributions will be drawn into relationship with Wittgenstein's philosophy of language as use, Melnyk's theory of causal levels of explanation, Korzybski's account of map and territory, the rejection of the heuristic rigidity of substantialist ontologies, and a cybernetics communication science-informed approach to contextual bi-directionality of causality. We thereby arrive at an understanding of Bateson's process psychology that, given its ecological-systemic nature, is explanatorily applicable across the mind sciences. This process psychology equips us to answer the question: What is mind? Not by explanatory appeal to substantial entities contained within mind, but instead by recourse to the contextually relevant patterns for understanding mind to a particular purpose. We have thereby attended to the gulf between heuristics and fundamentals, between psychological models and an onto-epistemic account of reality. Insufficient attention has been given to characterising the vital nature of Bateson's philosophical oeuvre to psychological practice. This article draws out Bateson's relevance to establishing foundational principles for a process psychology capable of reinvigorating psychological thought. (shrink)

This essay presents the conditional probability of co-contribution account of the individuation of cognitive systems (CPC) and argues that CPC provides an attractive basis for a theory of the cognitive self. The argument proceeds in a largely indirect way, by emphasizing empirical challenges faced by an approach that relies entirely on predictive processing (PP) mechanisms to ground a theory of the cognitive self. Given the challenges faced by PP-based approaches, we should prefer a theory of the cognitive self of the (...) sort CPC offers, one that accommodates variety in the kinds of mechanism that, when integrated, constitute a cognitive system (and thus the cognitive self), to a theory according to which the cognitive self is composed of essentially one kind of thing, for instance, prediction-error minimization mechanisms. The final section focuses on one of the central functions of the cognitive self: to engage in conscious reasoning. It is argued that the phenomenon of conscious, deliberate reasoning poses an apparently insoluble problem for a PP-based view, one that seems to rest on a structural limitation of predictive-processing models. In a nutshell, conscious reasoning is a single-stream phenomenon, but, in order for PP to apply, two streams of activity must be involved, a prediction stream and an input stream. Thus, with regard to the question of the nature of the self, PP-based views must yield to an alternative approach, regardless of whether proponents of the predictive processing, as a comprehensive theory of cognition, can handle the various empirical challenges canvassed in the preceding section. (shrink)

Games of chance are developed in their physical consumer-ready form on the basis of mathematical models, which stand as the premises of their existence and represent their physical processes. There is a prevalence of statistical and probabilistic models in the interest of all parties involved in the study of gambling – researchers, game producers and operators, and players – while functional models are of interest more to math-inclined players than problem-gambling researchers. In this paper I present a structural analysis of (...) the knowledge attached to mathematical models of games of chance and the act of modeling, arguing that such knowledge holds potential in the prevention and cognitive treatment of excessive gambling, and I propose further research in this direction. (shrink)

ABSTRACT Is there something specific about modelling that distinguishes it from many other theoretical endeavours? We consider Michael Weisberg’s thesis that modelling is a form of indirect representation through a close examination of the historical roots of the Lotka–Volterra model. While Weisberg discusses only Volterra’s work, we also study Lotka’s very different design of the Lotka–Volterra model. We will argue that while there are elements of indirect representation in both Volterra’s and Lotka’s modelling approaches, they are largely due (...) to two other features of contemporary model construction processes that Weisberg does not explicitly consider: the methods-drivenness and outcome-orientedness of modelling. 1Introduction 2Modelling as Indirect Representation 3The Design of the Lotka–Volterra Model by Volterra 3.1Volterra’s method of hypothesis 3.2The construction of the Lotka–Volterra model by Volterra 4The Design of the Lotka–Volterra Model by Lotka 4.1Physical biology according to Lotka 4.2Lotka’s systems approach and the Lotka–Volterra model 5Philosophical Discussion: Strategies and Tools of Modelling 5.1Volterra’s path from the method of isolation to the method of hypothesis 5.2The template-based approach of Lotka 5.3Modelling: methods-driven and outcome-oriented 6Conclusion. (shrink)

Studies in the psychology of visual expertise have tended to focus on a limited set of expert domains, such as radiology and athletics. Conclusions drawn from these data indicate that experts use parafoveal vision to process images holistically. In this study, we examined a novel, as-of-yet-unstudied class of visual experts—architects—expecting similar results. However, the results indicate that architects, though visual experts, may not employ the holistic processing strategy observed in their previously studied counterparts. Participants (n = 48, 24 architects, (...) 24 naïve) were asked to find targets in chest radiographs and perspective images. All images were presented in both gaze-contingent and normal viewing conditions. Consistent with a holistic processing model, we expected two results: (1) architects would display a greater difference in saccadic amplitude between the gaze- contingent and normal conditions, and (2) architects would spend less time per search than an undergraduate control group. We found that the architects were more accurate in the perspectival task, but they took more time and displayed a lower difference in saccadic amplitude than the controls. Our research indicates a disjunctive conclusion. Either architects are simply different kinds of visual experts than those previously studied, or we have generated a task that employs visual expertise without holistic processing. Our data suggest a healthy skepticism for across-the-board inferences collected from a single domain of expertise to the nature of visual expertise generally. More work is needed to determine whether holism is a feature of all visual expertise. (shrink)

Organismic agency is often understood as the capacity to produce goal-directed behavior. This paper proposes a new way of modelling agency, namely as a naturalized deliberation. Deliberative action is not directed towards a particular goal, but involves a process of weighing multiple goals and a choice for a particular combination of these. The underlying causal model is symmetry breaking, where the organism breaks symmetries present in the selective environment. Deliberation is illustrated though the phenomena of mate choice and (...) bacterial chemotaxis. (shrink)

The starting point of this paper is the idea that linguistic representation is the result of a global process: a process of interaction of a community of cognitive-linguistic agents, with one another and with the environment. I maintain that the study of truth, meaning and related notions should be addressed without losing perspective of this process, and I oppose the ‘static’ or ‘analytic’ approach, which is fundamentally based on our own knowledge of the conventional meaning of words (...) and sentences, and the ability of using them that we have as competent speakers. I argue that the analytic perspective is responsible for five recurring difficulties in truthmaker theory: (1) the lack of attention to the difference of explanatory role between the distinct notions proposed as primary truthbearer; (2) the adscription of purely extra-linguistic truthmakers to ‘synthetic truths’, ignoring the contribution of the linguistic factor; (3) the adscription of purely linguistic truthmakers to ‘logical’ and ‘analytic truths’, ignoring the contribution of the worldly factor; (4) the difficulties in the search for minimal truthmakers; (5) the problems in the treatment of ‘negative facts’ and of other ‘logically complex facts’. I do not provide an account of how to solve these difficulties, but I do show how the ‘process model’ helps to clear up confusion regarding them. (shrink)

This paper is devoted to some generalizations of explanatory potential of connectionist approaches to theoretical problems of the philosophy of mind. Are considered both strong, and weaknesses of neural network models. Connectionism has close methodological ties with modern neurosciences and neurophilosophy. And this fact strengthens its positions, in terms of empirical naturalistic approaches. However, at the same time this direction inherits weaknesses of computational approach, and in this case all system of anticomputational critical arguments becomes applicable to the connectionst models (...) of mind. The last developments in the field of deep learning gave rich empirical material for cognitive sciences. Multilayered networks, mathematical models of associative dynamics of learning, self-organizing neuronets and all that allow to explain the principles of human conceptual organizing and after this to emulate these processes in computer systems. At all engineering achievements of this technology there is a traditional criticism from representatives of cognitive psychology who cannot accept a thesis about learning ability of a neuronet on the basis of redistribution of scales. Process of learning of natural intelligence, according to cognitive models, happens due to attraction of knowledge broadcast in a symbolical form (mental representations, concepts) at the expense of the systems of output knowledge expressed in the propositional contents. Some philosophical aspects of «neural metaphor» in modern cognitive sciences create the problem field which demands comprehensive understanding, the first step towards which is taken in this work. (shrink)

Standard linguistic analysis of syntax uses the T-model. This model requires the ordering: D-structure > S-structure > LF, where D-structure is the sentences deep structure, S-structure is its surface structure, and LF is its logical form. Between each of these representations there is movement which alters the order of the constituent words; movement is achieved using the principles and parameters of syntactic theory. Psychological analysis of sentence production is usually either serial or connectionist. Psychological serial models do not (...) accommodate the T-model immediately so that here a new model called the P-model is introduced. The P-model is different from previous linguistic and psychological models. Here it is argued that the LF representation should be replaced by a variant of Frege'sA three qualities (sense, reference, and force), called the FregeA representation or F-representation. In the F-representation the order of elements is not necessarily the same as that in LF and it is suggested that the correct ordering is: F-representation > D-structure > S-structure. This ordering appears to lead to a more natural view of sentence production and processing. Within this framework movement originates as the outcome of emphasis applied to the sentence. The requirement that the F-representation precedes the D-structure needs a picture of the particular principles and parameters which pertain to movement of words between representations. In general this would imply that there is a preferred or optimal ordering of the symbolic string in the F-representation. The standard ordering is retained because the general way of producing such an optimal ordering is unclear. In this case it is possible to produce an analysis of movement between LF and D-structure similar to the usual analysis of movement between S-structure and LF. The necessity of analyzing corrupted data suggests that a maximal amount of information about a language's grammar and lexicon is stored. (shrink)

Learning is fundamentally about action, enabling the successful navigation of a changing and uncertain environment. The experience of pain is central to this process, indicating the need for a change in action so as to mitigate potential threat to bodily integrity. This review considers the application of Bayesian models of learning in pain that inherently accommodate uncertainty and action, which, we shall propose are essential in understanding learning in both acute and persistent cases of pain.

People often assume that everyone can be divided by sex/gender (that is, by physical and social characteristics having to do with maleness and femaleness) into two tidy categories: male and female. Careful thought, however, leads us to reject that simple ‘binary’ picture, since not all people fall precisely into one group or the other. But if we do not think of sex/gender in terms of those two categories, how else might we think of it? Here I consider four distinct models; (...) each model correctly captures some features of sex/gender, and so each is appropriate in some contexts. But the first three models are inadequate when tough questions arise, like whether trans women should be admitted as students at a women’s college or when it is appropriate for intersex athletes to compete in women’s athletic events. (‘Trans’ refers to the wide range of people who have an atypical gender identity for someone of their birth-assigned sex, and ‘intersex’ refers to people whose bodies naturally develop with markedly different physical sex characteristics than are paradigmatic of either men or women.) Such questions of inclusion and exclusion matter enormously to the people whose lives are affected by them, but ordinary notions of sex/gender offer few answers. The fourth model I describe is especially designed to make those hard decisions easier by providing a process to clarify what matters. (shrink)

Discussing theories at length, including their origin, development, and replacement by other theories, can help students in understanding of both objective and subjective aspects of the scientific process. Presenting theories in the form of- models helps in this undertaking, and the history of science provides a number of suitable models. The paper describes specific examples that have been used in in-service courses for science teachers.

The goal of this short chapter, aimed at philosophers, is to provide an overview and brief explanation of some central concepts involved in predictive processing (PP). Even those who consider themselves experts on the topic may find it helpful to see how the central terms are used in this collection. To keep things simple, we will first informally define a set of features important to predictive processing, supplemented by some short explanations and an alphabetic glossary. -/- The features described here (...) are not shared in all PP accounts. Some may not be necessary for an individual model; others may be contested. Indeed, not even all authors of this collection will accept all of them. To make this transparent, we have encouraged contributors to indicate briefly which of the features are necessary to support the arguments they provide, and which (if any) are incompatible with their account. For the sake of clarity, we provide the complete list here, very roughly ordered by how central we take them to be for “Vanilla PP” (i.e., a formulation of predictive processing that will probably be accepted by most researchers working on this topic). More detailed explanations will be given below. Note that these features do not specify individually necessary and jointly sufficient conditions for the application of the concept of “predictive processing”. All we currently have is a semantic cluster, with perhaps some overlapping sets of jointly sufficient criteria. The framework is still developing, and it is difficult, maybe impossible, to provide theory-neutral explanations of all PP ideas without already introducing strong background assumptions. (shrink)

Philosophers interested in the theoretical consequences of predictive processing often assume that predictive processing is an inferentialist and representationalist theory of cognition. More specifically, they assume that predictive processing revolves around approximated Bayesian inferences drawn by inverting a generative model. Generative models, in turn, are said to be structural representations: representational vehicles that represent their targets by being structurally similar to them. Here, I challenge this assumption, claiming that, at present, it lacks an adequate justification. I examine the only (...) argument offered to establish that generative models are structural representations, and argue that it does not substantiate the desired conclusion. Having so done, I consider a number of alternative arguments aimed at showing that the relevant structural similarity obtains, and argue that all these arguments are unconvincing for a variety of reasons. I then conclude the paper by briefly highlighting three themes that might be relevant for further investigation on the matter. (shrink)

Predictive processing (PP) has been repeatedly presented as a unificatory account of perception, action, and cognition. In this paper, we argue that this is premature: As a unifying theory, PP fails to deliver general, simple, homogeneous, and systematic explanations. By examining its current trajectory of development, we conclude that PP remains only loosely connected both to its computational framework and to its hypothetical biological underpinnings, which makes its fundamentals unclear. Instead of offering explanations that refer to the same set of (...) principles, we observe systematic equivocations in PP‐based models, or outright contradictions with its avowed principles. To make matters worse, PP‐based models are seldom empirically validated, and they are frequently offered as mere just‐so stories. The large number of PP‐based models is thus not evidence of theoretical progress in unifying perception, action, and cognition. On the contrary, we maintain that the gap between theory and its biological and computational bases contributes to the arrested development of PP as a unificatory theory. Thus, we urge the defenders of PP to focus on its critical problems instead of offering mere re‐descriptions of known phenomena, and to validate their models against possible alternative explanations that stem from different theoretical assumptions. Otherwise, PP will ultimately fail as a unified theory of cognition. (shrink)

John Broome has developed an account of rationality and reasoning which gives philosophical foundations for choice theory and the psychology of rational agents. We formalize his account into a model that differs from ordinary choice-theoretic models through focusing on psychology and the reasoning process. Within that model, we ask Broome’s central question of whether reasoning can make us more rational: whether it allows us to acquire transitive preferences, consistent beliefs, non-akratic intentions, and so on. We identify three (...) structural types of rationality requirements: consistency requirements, completeness requirements, and closedness requirements. Many standard rationality requirements fall under this typology. Based on three theorems, we argue that reasoning is successful in achieving closedness requirements, but not in achieving consistency or completeness requirements. We assess how far our negative results reveal gaps in Broome's theory, or deficiencies in choice theory and behavioral economics. (shrink)

We can illustrate the phenomenon of model-induced escape by examining the phenomenon of spam filters. Spam filter A is, we can assume, very effective at blocking spam. Indeed it is so effective that it motivates the authors of spam to invent new types of spam that will beat the filters of spam filter A. -/- An example of this phenomenon in the realm of philosophy is illustrated in the work of Nyíri on Wittgenstein's political beliefs. Nyíri writes a paper (...) demonstrating convincingly that there are strong signals of a conservative strain of thought in the writings of Wittgenstein. This has initially a tiny effect; but then a more significant effect sets in as the authors of Wittgenstein secondary literature, consciously or unconsciously, draw attention to features of Wittgenstein which cast the conservatism thesis in a negative light. This is an example of what I call model-induced escape: the Nyíri model of Wittgenstein initiates a process which undermines the Nyíri model of Wittgenstein. -/- Wittgenstein, as obiectum philosophiae, is reduced to a constantly mutating set of interpretations of a certain body of work. -/- Perhaps this is what makes philosophy so problematic when viewed from the perspective of results, or in other words of signs of progress commonly accepted across the discipline. There are just too many ways of inducing escape from any given putative discovery; too many dimensions along which an interpretative or definitional arms race can be triggered. (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.