Professor Apter has written a valuable book. His work, a non-technical introduction to the most important aspect of the use of computers in psychology, is simple, readable, yet surprisingly concentrated and provocative. His first two chapters contain an unusually clear, concise examination of the extent to which minds and machines can be compared. Although brief it successfully collates the work of famous scientists and scholars of varied disciplines into a coherent cybernetic theory. Chapter three is a simplified explanation of (...) the way a digital computer works. This serves as a handy reference for the layman during more difficult discussions in ensuing chapters. Chapters four through nine recount the progress of many researchers in copying human behavior by means of machines. Here Apter examines data that have been part of the literature of computer simulation for some time, such as the Turing test, the General Problem Solver, experiments in Pattern Recognition, etc. But he also treats new or heretofore unnoticed research which undoubtedly will become elements in future philosophical controversy. One of these new cases is a program written by J. C. Loehlin called "Aldous". Aldous is the name given individually to a number of programs which interact emotionally. Loehlin so far has programmed anAldous, Decisive and Hesitant Aldouses, and, finally, Radical and Conservative Aldouses. Although the Aldous programs may sound more amusing than sober research in this area should, the details of the programming are both fascinating and philosophically significant. Loehlin, for instance, is forced to define "emotion" strictly in terms of environmental cues and elementary behavioral parameters. However, his Aldouses achieve from this a quite impressive and sophisticated repertoire of emotional responses accounting for learning, consistent emotional responses to unknown objects, mixed emotions, moods, frustration, satisfaction. Indeed, an "experienced" Aldous will exhibit behavior as unpredictable as any human. However, one still hesitates to call these reactions "emotion." Besides the obvious lack of physiological responses Aldous has no control over his environment and a merely marginal control over his emotions. Apter sees this difficulty clearly: "In particular one would like to see added the possibility of Aldous planning rather than reacting to the current situation and also the possibility of... changing not only his attitudes but also the parameters which govern the acquisition and change of attitudes." This criticism also may be levelled against other better known "personality" programs based on individual personality theories such as Heider’s or Homan’s. Apter clearly perceives theoretical difficulties in computer simulation such as these. Always, he faces them and gauges their relevance for the explanation of human behavior. The one serious shortcoming of Apter’s book is its brevity. Especially when he struggles with the theoretical implications of a particular experiment one gets the impression that he is needlessly condensing his analysis. This is particularly noticeable in the last chapter where he presents in barely-fleshed outline his position on the problem of consciousness. Despite this difficulty, however, Apter has fulfilled quite ably a promise he made in his preface that: "... this book about computers will be of interest to students of psychology and philosophy, the general reader and... perhaps also one day to computers."—J. F. (shrink)

Using four examples of models and computer simulations from the history of psychology, I discuss some of the methodological aspects involved in their construction and use, and I illustrate how the existence of a model can demonstrate the viability of a hypothesis that had previously been deemed impossible on a priori grounds. This shows a new way in which scientists can learn from models that extends the analysis of Morgan (1999), who has identified the construction and manipulation of (...) models as those phases in which learning from models takes place. (shrink)

Scientificity is essentially methodology. The use of information technology as methodological instruments in science has been increasing for decades, this raises the question: Does this transform science? This question is the subject of the Special Issue in Minds and Machines “The epistemological significance of methods in computer simulation and machine learning”. We show that there is a technological change in this area that has three methodological and epistemic consequences: methodological opacity, reproducibility issues, and altered forms of justification.

The papers included are divided into five sections: Psychology and Philosophy of Perception and Discovery, Integrations of Experimental Findings, Theoretical Developments, Experimental Results from Neurophysiology and Psychology Pertinent to Model Building, and Computer Simulations of Complex Models. The last of these sections will probably prove most interesting to the contemporary philosopher of mind. Peirce, Cassirer, and Wittgenstein are the philosophers who make the scene in the first section; inclusion of material from the last of these is no (...) mean editorial feat. The volume aims to be comprehensive rather than intensive and while this makes it ideal for the philosopher, the psychologist may find it thin in spots.—E. A. R. (shrink)

Some researchers claim that simulations of the emergence of communication in populations of autonomous agents provide empirical support for 'use' theories of meaning. I argue that this claim faces at least two major challenges. First, the empirical adequacy of such simulations must be justified, or the inference from simulation results to real-world linguistic behavior must be dropped; and second, the proffered simulations are in fact compatible with all of the competing theories of meaning surveyed, suggesting that theories of meaning (...) are not the kinds of theories for which simulations provide evidence. To conclude, I consider what impact this has on the project of developing a naturalized theory of language. (shrink)

In the last decades, the evidence-based approach has become dominant in the biomedical sciences. Its influence has extended from clinical practice to other areas such as drug regulation and public health. Nonetheless, given the limitations of the evidence-based framework, a more pluralist approach towards evidence has been demanded. In this sense, evidential pluralism holds that evidence of mechanisms should complement statistical evidence. This paper aims to explore and discuss the prospects of evidential pluralism in public health. First, we will analyse (...) the evidential standards of the International Agency for Research on Cancer. Those standards are argued to be in line with the pluralist approach. Second, we will consider the main challenges for gathering evidence of mechanisms in public health. For that purpose, diverse types of evidence of mechanisms will be identified. And third, we will assess the role of agent-based models as mechanistic studies. Based on a case study, we will discuss whether agent-based models can provide evidence of mechanisms and mitigate the abovementioned challenges. (shrink)

In this article, I focus on the role of computer simulations as exploratory strategies. I begin by establishing the non-theory-driven nature of simulations. This refers to their ability to characterize phenomena without relying on a predefined conceptual framework that is provided by an implemented mathematical model. Drawing on Steinle’s notion of exploratory experimentation and Gelfert’s work on exploratory models, I present three exploratory strategies for computer simulations: (1) starting points and continuation of scientific inquiry, (2) varying the parameters, (...) and (3) scientific prototyping. (shrink)

Viewed from an evolutionary standpoint, emotions can be understood as situation-specific patterns of energy consumption related to behaviors that have been selected by evolution for their survival value, such as environmental exploration, flight or fight, and socialization. In the present article, the energy linked with emotions is investigated by a strictly energy-based simulation of the evolution of simple autonomous agents provided with random cognitive and motor capacities and operating among food and predators. Emotions are translated into evolving patterns of (...) energy consumption related to situation-specific behaviors. As a result, a variety of behaviors resembling emotions emerge, each with a specific pattern of energy consumption. There is little difference between emotion-like behaviors on individual and collective levels. The fact that these patterns evolve under a strictly energetic selection regime indicates the interesting role and adaptive advantage of emotions as situation-specific energy savers. Although gained through an approach characterized by a highly reduced complexity, these findings support a quantitative understanding of emotions that may improve the existing qualitative approaches and could have far-reaching implications for further research on and conceptualization of emotions and their interactions with cognition. (shrink)

This study explores the dynamic feature of organizational citizenship behaviors under the condition of challenge stressors, as this has not been addressed by previous research. Combining the cybernetic theory of stress and social exchange theory, this study builds a dynamic computational model regarding the circular causality between challenge stressors and organizational citizenship behaviors. By conducting a series of simulation experiments, we validated and demonstrated important questions regarding organizational citizenship behaviors. Specifically, when both the initial value of challenge stressors and (...) the importance of challenge appraisal are higher, organizational citizenship behaviors tend to show a sharped inverted U shape at the early stage. When both the equilibrium level of job satisfaction and the initial value of challenge stressors are higher, organizational citizenship behaviors will show an inverted N shape over time. The number and frequency of assigned challenge tasks have an interactive effect on the accumulation of organizational citizenship behaviors within a period. Our theory contributes to identifying the dynamic relationship between challenge stressors and organizational citizenship behaviors. Findings from dynamic computational theory can offer suggestions for managers to encourage employees’ engagement in organizational citizenship behaviors. (shrink)

Intentionalism must be distinguished from computational psychology. The former is a mentalist-realist metatheoretical stance vis-a-vis the latter, which is a research programme devoted to the construction of informationally-characterized simulation models for human behavior, perception, cognition, etc. Intentionalism has its attractive aspects, but unfortunately it is plagued by severe conceptual difficulties. Recent attempts to justify the intentionalist interpretation of computational models, by J.A. Fodor and by C. Graves, J.J. Katz et al., fail to secure a conceptually adequate and genuinely (...) intentional sense for the intentional idiom they employ. (shrink)

Although Paul Churchland and Jerry Fodor both subscribe to the so-called theory-theory– the theory that folk psychology (FP) is an empirical theory of behavior – they disagree strongly about FP’s fate. Churchland contends that FP is a fundamentally flawed view analogous to folk biology, and he argues that recent advances in computational neuroscience and connectionist AI point toward development of a scientifically respectable replacement theory that will give rise to a new common-sense psychology. Fodor, however, wagers that FP (...) will be largely preserved and vindicated by scientific investigations of behavior. Recent findings by developmental psychologists, I argue, will push both Churchlandians and Fodorians toward the pessimistic view that FP is a misguided theory that will never be displaced, because it is, so to speak, built into our cognitive systems. I explore the possibility of preserving optimism by rejecting the theory-theory and adopting the simulation theory, a competing view developed by Robert Gordon, Alvin Goldman, and Jane Heal. According to simulationists, common-sense interpretation of behavior is accomplished by means of pretense-like operations that deploy the cognitive system’s own reasoning capabilities in a disengaged manner. Since on this view no theory-like set of principles would be needed, the simulation theory seems to enjoy a simplicity advantage over the theory-theory. Steven Stich and Shawn Nichols, however, contend that as the cognitive system would require special mechanisms for disengaged operation, the simplicity question cannot be resolved until suitable computational models are developed. I describe a set of models I have constructed to meet this need, and I discuss the contribution such models can make to determining FP’s fate. (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)

Scientific discovery is often regarded as romantic and creative - and hence unanalyzable - whereas the everyday process of verifying discoveries is sober and more suited to analysis. Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled. Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human (...) thought processes used to discover scientific laws. The programs - BACON, DALTON, GLAUBER, and STAHL - are all largely data-driven, that is, when presented with series of chemical or physical measurements they search for uniformities and linking elements, generating and checking hypotheses and creating new concepts as they go along. "Scientific Discovery examines the nature of scientific research and reviews the arguments for and against a normative theory of discovery; describes the evolution of the BACON programs, which discover quantitative empirical laws and invent new concepts; presents programs that discover laws in qualitative and quantitative data; and ties the results together, suggesting how a combined and extended program might find research problems, invent new instruments, and invent appropriate problem representations. Numerous prominent historical examples of discoveries from physics and chemistry are used as tests for the programs and anchor the discussion concretely in the history of science. Pat Langley is an Associate Professor in the Department of Information and Computer Science at the University of California, Irvine.Herbert Simon is a Professor in the Departments of Psychology, Computer Science, and Philosophy at Carnegie-Mellon University. Gary L. Bradshaw is an Assistant Professor in the Department of Psychology and Institute of Cognitive Science at the University of Colorado, Boulder. Jan M. Zytkow is an Associate Professor in the Computer Science Department at Wichita State University. (shrink)

Computational models can aid in the development of philosophical views concerning the structure and growth of scientific knowledge. In cognitive psychology, computational models have proved valuable for describing the structures and processes of thought and for testing these models by writing and running computer programs using the techniques of artificial intelligence. Similarly, in the philosophy of science models can be developed that shed light on the structure, discovery, and justification of scientific theories. This paper briefly describes a computational (...) model of problem solving and learning that has been used to simulate several kinds of scientific reasoning. (shrink)

Modeling is as old as humanity. It is one of the ways in which we experience the world, teach our children, and entertain ourselves. The digital computer, on the other hand, is approximately 60 years old but as computing power increases and access to technology becomes easier, more disciplines are using statistical and computational simulations. From the humanities to social sciences, scholars are advocating for a computational branch of their field of study. This is very exciting, and we want (...) to make sure that all disciplines stay connected and share their insights as they grow in their respective areas. Religion is a complex system that consists of humans, society, culture and social constructs that have evolved over millennia. The study of religion relies on empirical approaches to collect and analyze data to generate or validate existing theories. Modeling and simulation allows us to venture beyond statistical observation and into an exploration of the causal relationships between the different aspects of religion. It provides us with the ability to understand the system as a whole, the possibility of projecting how religion will evolve in the future and the capability to compare, contrast and merge seemingly conflicting theories of religion. In this article, we present five critical things that scholars in psychology of religion should know about the discipline of Modeling and Simulation. The goal of this short primer is to highlight the universal aspects of Modeling and Simulation and to provide a unifying view that transcends disciplines. (shrink)

Alvin I. Goldman, Simulating Minds: The Philosophy, Psychology and Neuroscience of Mindreading Content Type Journal Article Pages 279-282 DOI 10.1007/s11023-009-9142-x Authors Susan Stuart, University of Glasgow Humanities Advanced Technology and Information Institute 11 University Gardens Glasgow G12 8QQ Scotland, UK Journal Minds and Machines Online ISSN 1572-8641 Print ISSN 0924-6495 Journal Volume Volume 19 Journal Issue Volume 19, Number 2.

The Fukushima nuclear accident from 2011 provided an occasion for the public display of radiation maps generated using decision-support systems for nuclear emergency management. Such systems rely on computer models for simulating the atmospheric dispersion of radioactive materials and estimating potential doses in the event of a radioactive release from a nuclear reactor. In Germany, as in Japan, such systems are part of the national emergency response apparatus and, in case of accidents, they can be used by emergency task (...) forces for planning radioprotection countermeasures. In this context, the paper addresses the epistemology of dose projections by critically analyzing some of the sources of epistemic opacity and non-knowledge affecting them, and the different methods and practices used by German radioprotection experts to improve their trustworthiness and reliability. It will be argued that dose projections are part of an entire radioprotection regime or assemblage built around the belief that the effects of nuclear accidents can be effectively mitigated thanks to the simulation technologies underlying different protocols and practices of nuclear preparedness. And, as the Fukushima experience showed, some of these expectations will not be met in real emergencies due to the inherent uncertainties entailed by the use of dose projections when planning protective countermeasures. (shrink)

The phenomenon of consciousness has always been a central question for philosophers and scientists. Emerging in the past decade are new approaches to the understanding of consciousness in a scientific light. This book presents a series of essays by leading thinkers giving an account of the current ideas prevalent in the scientific study of consciousness. The value of the book lies in the discussion of this interesting though complex subject from different points of view ranging from physics, computer science (...) to the cognitive sciences. Reviews of controversial ideas related to the philosophy of mind from western and eastern sources including classical Indian first person methodologies provide a breadth of coverage that has seldom been attempted in a book before. Additionally, chapters relating to the new approaches in computational modelling of higher order cognitive function and consciousness are included. The book is of great value for established as well as young researchers from a wide cross-section of interdisciplinary scientific backgrounds, aiming to pursue research in this field, as well as an informed public. * Presents the latest developments in the scientific study of consciousness * Critically reviews different theoretical and philosophical explanations related to the subject * An important book for both students and researchers in designing research projects on consciousness. (shrink)

'Affective computing' is a branch of computing concerned with the theory and construction of machines which can detect, respond to, and simulate human emotional states. This book presents an interdisciplinary exploration of this rapidly expanding field, aimed at those in psychology, computational neuroscience, computer science, and AI. A Blueprint for Affective Computing: A sourcebook and manual is the very first attempt to ground affective computing within the disciplines of psychology, affective neuroscience, and philosophy. This book illustrates the (...) contributions of each of these disciplines to the development of the ever-growing field of affective computing. In addition, it demonstrates practical examples of cross-fertilization between disciplines in order to highlight the need for integration of computer science, engineering and the affective sciences. (shrink)

In this article we discuss the notion of a linguistic universal, and possible sources of such invariant properties of natural languages. In the first part, we explore the conceptual issues that arise. In the second part of the paper, we focus on the explanatory potential of horizontal evolution. We particularly focus on two case studies, concerning Zipf's Law and universal properties of color terms, respectively. We show how computer simulations can be employed to study the large scale, emergent, consequences (...) of psychologically and psychologically motivated assumptions about the working of horizontal language transmission. (shrink)

Mental or computer simulation of cause and effect of certain behaviors is a recognized approach to changing one’s attitude or triggering an action. Meanwhile, psychology research results suggest that frequency of simulation may affect the corresponding persuasiveness. This paper argues that with always-on sensing and data-driven visualization technologies, interactive tangible systems can be designed to simulate hypothetical outcomes of real-life behaviors in everyday contexts, which repeatedly stimulate users’ imagination of behavioral consequences and thereby behavioral intentions. To (...) investigate the effect, a working prototype of Incingarette, including a smart ashtray in connection with a digital picture frame, was built. When the ashtray is used for smoking, the digital picture is incrementally covered by virtual dust. Field trials involved participants in five daily smoking sessions. Post-session surveys show increasingly stronger perceived causality between smoking and the simulated outcomes, increasingly more vivid mental imagery of consequences, and increasingly intense intention to reduce smoking. Results suggest that repeatedly presenting simulated outcomes cognitively linked to real-life behaviors can increase behavioral intentions. (shrink)

Any analysis of the concept of computation as it occurs in the context of a discussion of the computational model of the mind must be consonant with the philosophic burden traditionally carried by that concept as providing a bridge between a physical and a psychological description of an agent. With this analysis in hand, one may ask the question: are connectionist-based systems consistent with the computational model of the mind? The answer depends upon which of several versions of connectionism one (...) presupposes: non-learning connectionist-based systems as simulated on digital computers are consistent with the computational model of the mind, whereas connectionist-based systems (/dynamical systems) qua analog systems are not. (shrink)

It is argued that the traditional distinction between artificial intelligence and cognitive simulation amounts to little more than a difference in style of research - a different ordering in goal priorities and different methodological allegiances. Both enterprises are constrained by empirical considerations and both are directed at understanding classes of tasks that are defined by essentially psychological criteria. Because of the different ordering of priorities, however, they occasionally take somewhat different stands on such issues as the power/generality trade-off and (...) on the relevance of the sort of data collected in experimental psychology laboratories. (shrink)

In this article we discuss the notion of a linguistic universal, and possible sources of such invariant properties of natural languages. In the first part, we explore the conceptual issues that arise. In the second part of the paper, we focus on the explanatory potential of horizontal evolution. We particularly focus on two case studies, concerning Zipf’s Law and universal properties of color terms, respectively. We show how computer simulations can be employed to study the large scale, emergent, consequences (...) of psychologically and psychologically motivated assumptions about the working of horizontal language transmission. (shrink)

Theories of mind draw on processes that represent mental states and their computational connections; simulation, in addition, draws on processes that replicate (Heal 1986 ) a sequence of mental states. Moreover, mental simulation can be triggered by input from imagination instead of real perceptions. To avoid confusion between mental states concerning reality and those created in simulation, imagined contents must be quarantined. Goldman bypasses this problem by giving pretend states a special role to play in simulation (...) (Goldman 2006 ). We argue that this path leads to the resurgence of the threat of collapse (Davies 1994 ), diluting the principled distinction between simulation and theory use. Exploration of a related method of real-mental states operating in a pretend mode leads to a factually untenable model. Our main goal here is to raise this problem as a challenge for Goldman’s reconfigured simulation theory. Only at the end we will briefly sketch a possible alternative way of quarantine that preserves the replicative element of simulation and avoids collapse. Figure 1 provides a guide to our argument. (shrink)

Counterfactual thinking involves the imagination of non-factual alternatives to reality. We investigated the spontaneous generation of both upward counterfactuals, which improve on reality, and downward counterfactuals, which worsen reality. All subjects gained $5 playing a computer-simulated blackjack game. However, this outcome was framed to be perceived as either a win, a neutral event, or a loss. "Loss" frames produced more upward and fewer downward counterfactuals than did either "win" or "neutral" frames, but the overall prevalence of counterfactual thinking did (...) not vary with outcome valence. In addition, subjects who expected to play the game again made more upward counterfactuals and were less satisfied with the outcome than were subjects who did not expect to play again. However, once subjects saw the cards from which they could have selected had they "hit" again (two winning cards and two losing cards), all subjects generated primarily upward counterfactuals and showed a corresponding decrease in satisfaction. These results implicate both cognitive and motivational factors in the generation of counterfactuals and tell us something about the functional value of counterfactual thinking: downward counterfactuals provide comfort; upward counterfactuals prepare one for the future. (shrink)

This study explored spatial navigation alongside several other cognitive abilities that are thought to share common underlying neurocognitive mechanisms (e.g., the capacity for self-projection, scene construction, or mental simulation), and which we hypothesised may be impaired in autism spectrum disorder (ASD). Twenty intellectually high-functioning children with ASD (with a mean age of ~8 years) were compared to 20 sex, age, IQ, and language ability matched typically developing children on a series of tasks to assess spatial navigation, episodic memory, episodic (...) future thinking (also known as episodic foresight or prospection), theory of mind, relational memory, and central coherence. This is the first study to explore these abilities concurrently within the same sample. Spatial navigation was assessed using the “memory island” task, which involves finding objects within a realistic, computer simulated, three-dimensional environment. Episodic memory and episodic future thinking were assessed using a past and future event description task. Theory of mind was assessed using the “animations” task, in which children were asked to describe the interactions between two animated triangles. Relational memory was assessed using a recognition task involving memory for items (line drawings), patterned backgrounds, or combinations of items and backgrounds. Central coherence was assessed by exploring differences in performance across segmented and unsegmented versions of block design. Children with ASD were found to show impairments in spatial navigation, episodic memory, episodic future thinking, and central coherence, but not theory of mind or relational memory. Among children with ASD, spatial navigation was found to be significantly negatively related to number of repetitive behaviours. In other words, children who showed more repetitive behaviours showed poorer spatial navigation. The theoretical and practical implications of the results are discussed. (shrink)

Computational models of emotions have been thriving and increasingly popular since the 1990s. Such models used to be concerned with the emotions of individual agents when they interact with other agents. Out of the array of models for the emotions, we are going to devote special attention to the approach in Adamatzky’s Dynamics of Crowd-Minds. The reason it stands out, is that it considers the crowd, rather than the individual agent. It fits in computational intelligence. It works by mathematical (...) class='Hi'>simulation on a crowd of simple artificial agents: by letting the computer program run, the agents evolve, and crowd behaviour emerges. Adamatzky’s purpose is to give an account of the emergence of allegedly “irrational” behaviour. This is not without problem, as the irrational to one person may seem entirely rational to another, and this in turn is an insight that, in the history of crowd psychology, has affected indeed the competition among theories of crowd dynamics. Quite importantly, Adamatzky’s book argues for the transition from individual agencies to a crowd’s or a mob’s coalesced mind as so, and at any rate for coalesced crowd’s agency. (shrink)

Knauff and Gazzo Castañeda (2022) object to using the term “new paradigm” to describe recent developments in the psychology of reasoning. This paper concedes that the Kuhnian term “paradigm” may be queried. What cannot is that the work subsumed under this heading is part of a new, progressive movement that spans the brain and cognitive sciences: Bayesian cognitive science. Sampling algorithms and Bayes nets used to explain biases in JDM can implement the Bayesian new paradigm approach belying any advantages (...) of mental models theory (MMT) at the algorithmic level. Moreover, this paper argues that new versions of MMT lack a computational level theory and questions the grounds for MMTs much-vaunted generality. The paper then examines common ground on the importance of small-scale models/simulations of the world and the importance of argumentation in the social domain rather than individual reasoning. Finally, the paper concludes that although there may be prospects for moving reasoning research forward in a more collective, collaborative manner, many disagreements remain to be resolved. (shrink)

Modelling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain's operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders (...) of consciousness, e.g. Coma, Vegetative State/Unresponsive Wakefulness Syndrome, Minimally Conscious State.Notwithstanding their technical limitations, we suggest that simulation technologies may offer new solutions to old practical problems, particularly in clinical contexts. We take DOCs as an illustrative case, arguing that the simulation of neural correlates of consciousness is potentially useful for improving treatments of patients with DOCs. (shrink)

The use of modeling and simulation methodologies is growing rapidly across the psychological and social sciences. After a brief introduction to the relevance of computational methods for research on human cognition and culture, we describe the sense in which computer models and simulations can be understood, respectively, as “theories” and “predictions.” Most readers of JoCC are interested in integrating micro- and macro-level theories and in pursuing empirical research that informs scientific predictions, and we argue that M&S provides a (...) powerful new set of tools for pursuing these interests. We also point out the way in which M&S can help scholars of cognition and culture address four key desiderata for social scientific research related to the themes of clarity, falsifiability, dynamicity, and complexity. Finally, we provide an introduction to the other papers that comprise this special issue, which includes contributions on topics such as the role of M&S in interdisciplinary debates, shamanism, early Christian ritual practices, the emergence of the Axial age, and the social scientific appropriation of algorithms from massively multiplayer online games. (shrink)

Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisficing, the authors have proposed a family of algorithms based on a simple psychological mechanism: one-reason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer (...) class='Hi'>simulation, the authors held a competition between the satisficing "Take The Best" algorithm and various "rational" inference procedures. The Take The Best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference. (shrink)

How might philosophy of religion be impacted by developments in computational modeling and social simulation? After briefly describing some of the content and context biases that have shaped traditional philosophy of religion, this article provides examples of computational models that illustrate the explanatory power of conceptually clear and empirically validated causal architectures informed by the bio-cultural sciences. It also outlines some of the material implications of these developments for broader metaphysical and metaethical discussions in philosophy. Computer modeling and (...) simulation can contribute to the reformation of the philosophy of religion in at least three ways: by facilitating conceptual clarity about the role of biases in the emergence and maintenance of phenomena commonly deemed “religious,” by supplying tools that enhance our capacity to link philosophical analysis and synthesis to empirical data in the psychological and social sciences, and by providing material insights for metaphysical hypotheses and metaethical proposals that rely solely on immanent resources. (shrink)

Children’s cognitive control and knowledge at school entry predict growth rates in analogical reasoning skill over time; however, the mechanisms by which these factors interact and impact learning are unclear. We propose that inhibitory control (IC) is critical for developing both the relational representations necessary to reason and the ability to use these representations in complex problem solving. We evaluate this hypothesis using computational simulations in a model of analogical thinking, Discovery of Relations by Analogy/Learning and Inference with Schemas and (...) Analogy (DORA/LISA; Doumas et al., 2008 ). Longitudinal data from children who solved geometric analogy problems repeatedly over 6 months show three distinct learning trajectories though all gained somewhat: analogical reasoners throughout, non-analogical reasoners throughout, and transitional – those who start non-analogical and grew to be analogical. Varying the base level of top-down lateral inhibition in DORA affected the model’s ability to learn relational representations, which, in conjunction with inhibition levels used in LISA during reasoning, simulated accuracy rates and error types seen in the three different learning trajectories. These simulations suggest that IC may not only impact reasoning ability but may also shape the ability to acquire relational knowledge given reasoning opportunities. (shrink)

African literature has played a major role in changing and shaping perceptions about African people and their way of life for the longest time. Unlike western cultures that are associated with advanced forms of writing, African literature is oral in nature, meaning it has to be recited and even performed. Although Africa has an old tribal culture, African philosophy is a new and strange idea among us. Although the problem of “universality” of African philosophy actually refers to the question of (...) whether Africa has heckling of philosophy in the Western sense, obviously, the philosophy bred by Africa’s native culture must be acknowledged. Therefore, the human–computer interaction-oriented method is proposed to appreciate African literature and African philosophy. To begin with, a physical object of tablet-aid is designed, and a depth camera is used to track the user’s hand and tablet-aid and then map them to the virtual scene, respectively. Then, a tactile redirection method is proposed to meet the user’s requirement of tactile consistency in head-mounted display virtual reality environment. Finally, electroencephalogram emotion recognition, based on multiscale convolution kernel convolutional neural networks, is proposed to appreciate the reflection of African philosophy in African literature. The experimental results show that the proposed method has a strong immersion and a good interactive experience in navigation, selection, and manipulation. The proposed HCI method is not only easy to use, but also improves the interaction efficiency and accuracy during appreciation. In addition, the simulation of EEG emotion recognition reveals that the accuracy of emotion classification in 33-channel is 90.63%, almost close to the accuracy of the whole channel, and the proposed algorithm outperforms three baselines with respect to classification accuracy. (shrink)

People recognize faces of their own race more accurately than faces of other races. The “contact” hypothesis suggests that this “other‐race effect” occurs as a result of the greater experience we have with own‐ versus other‐race faces. The computational mechanisms that may underlie different versions of the contact hypothesis were explored in this study. We replicated the other‐race effect with human participants and evaluated four classes of computational face recognition algorithms for the presence of an other‐race effect. Consistent with the (...) predictions of a developmental contact hypothesis, “experience‐based models” demonstrated an other‐race effect only when the representational system was developed through experience that warped the perceptual space in a way that was sensitive to the overall structure of the model's experience with faces of different races. When the model's representation relied on a feature set optimized to encode the information in the learned faces, experience‐based algorithms recognized minority‐race faces more accurately than majority‐race faces. The results suggest a developmental learning process that warps the perceptual space to enhance the encoding of distinctions relevant for own‐race faces. This feature space limits the quality of face representations for other‐race faces. (shrink)

One of the most debated questions in psychology and cognitive science is the nature and the functioning of the mental processes involved in deductive reasoning. However, all existing theories refer to a specific deductive domain, like syllogistic, propositional or relational reasoning.Our goal is to unify the main types of deductive reasoning into a single set of basic procedures. In particular, we bring together the microtheories developed from a mental models perspective in a single theory, for which we provide a (...) formal foundation. We validate the theory through a computational model (UNICORE) which allows fine‐grained predictions of subjects' performance in different reasoning domains.The performance of the model is tested against the performance of experimental subjects—as reported in the relevant literature—in the three areas of syllogistic, relational and propositional reasoning. The computational model proves to be a satisfactory artificial subject, reproducing both correct and erroneous performance of the human subjects. Moreover, we introduce a developmental trend in the program, in order to simulate the performance of subjects of different ages, ranging from children (3–6) to adolescents (8–12) to adults (>21). The simulation model performs similarly to the subjects of different ages.Our conclusion is that the validity of the mental model approach is confirmed for the deductive reasoning domain, and that it is possible to devise a unique mechanism able to deal with the specific subareas. The proposed computational model (UNICORE) represents such a unifying structure. (shrink)

Cognitive studies of science and technology have had a long history of largely independent research projects that have appeared in multiple outlets, but rarely together. The emergence of a new International Society for Psychology of Science and Technology suggests that this is a good time to put some of the latest work in this area into topiCS in a way that will both acquaint readers with the cutting edge in this domain and also give them a hint of its (...) history. One core theme includes how scientists, inventors, and engineers represent and solve problems; another, related theme is the extent to which they distribute and share cognition. Methodologies include fine‐grained studies of historical records, protocols of working scientists, observations and comparisons of engineering science laboratories, and computational simulations designed both to serve as research tools and also to improve scientific problem‐solving. The series of articles will conclude with the Associate Editor’s suggestions for future research. (shrink)

Recently, the mechanistic framework of active inference has been put forward as a principled foundation to develop an overarching theory of consciousness which would help address conceptual disparities in the field (Wiese 2018 ; Hohwy and Seth 2020 ). For that promise to bear out, we argue that current proposals resting on the active inference scheme need refinement to become a process theory of consciousness. One way of improving a theory in mechanistic terms is to use formalisms such as computational (...) models that implement, attune and validate the conceptual notions put forward. Here, we examine how computational modelling approaches have been used to refine the theoretical proposals linking active inference and consciousness, with a focus on the extent and success to which they have been developed to accommodate different facets of consciousness and experimental paradigms, as well as how simulations and empirical data have been used to test and improve these computational models. While current attempts using this approach have shown promising results, we argue they remain preliminary in nature. To refine their predictive and structural validity, testing those models against empirical data is needed i.e., new and unobserved neural data. A remaining challenge for active inference to become a theory of consciousness is to generalize the model to accommodate the broad range of consciousness explananda; and in particular to account for the phenomenological aspects of experience. Notwithstanding these gaps, this approach has proven to be a valuable avenue for theory advancement and holds great potential for future research. (shrink)

The purpose is to improve the teaching quality of Russian spatial prepositions in colleges. This work takes teaching Russian spatial prepositions as an example to study the key technologies in 3D Virtual Simulation teaching. 3D VS situational teaching is a high-end visual teaching technology. VS situation construction focuses on Human-Computer Interaction to explore and present a realistic language teaching scene. Here, the Steady State Visual Evoked Potential is used to control Brain-Computer Interface. An SSVEP-BCI system is constructed (...) through the Hybrid Frequency-Phase Modulation. The acquisition system can obtain the current SSVEP from the user's brain to know which module the user is watching to complete instructions encoded by the module. Experiments show that the recognition accuracy of the proposed SSVEP-BCI system based on HFPM increases with data length. When the data length is 0.6-s, the Information Transfer Rate reaches the highest: 242.21 ± 46.88 bits/min. Therefore, a high-speed BCI character input system based on SSVEP is designed using HFPM. The main contribution of this work is to build a SSVEP-BCI system based on joint frequency phase modulation. It is better than the currently-known brain computer interface character input system, and is of great value to optimize the performance of the virtual simulation situation system for Russian spatial preposition teaching. (shrink)

Computer simulation models of mentality and brain theory each, confront a challenge that they do not account for all the data of psychology: the category of contents of consciousness, as a phenomenologist would call it, seems completely untouched by these physicalistic analyses. In my paper I provide a sketch of a possible approach to explaining conditions for ascription of consciousness which is compatible with computer-theoretic and brain-theoretic models.