Drawing on recent findings, this study examines whether valence concordant electromyography (EMG) responses can be explained as an unconditional effect of mere stimulus processing or as somatosensory simulation driven by task-dependent processing strategies. While facial EMG over the Corrugator supercilii and the Zygomaticus major was measured, each participant performed two tasks with pictures of album covers. One task was an affective evaluation task and the other was to attribute the album covers to one of five decades. The Embodied Emotion (...) Account predicts that valence concordant EMG is more likely to occur if the task necessitates a somatosensory simulation of the evaluative meaning of stimuli. Results support this prediction with regard to Corrugator supercilii in that valence concordant EMG activity was only present in the affective evaluation task but not in the non-evaluative task. Results for the Zygomaticus major were ambiguous. Our findings are in line with the view that EMG activity is an embodied part of the evaluation process and not a mere physical outcome. (shrink)

People are minded creatures; we have thoughts, feelings and emotions. More intriguingly, we grasp our own mental states, and conduct the business of ascribing them to ourselves and others without instruction in formal psychology. How do we do this? And what are the dimensions of our grasp of the mental realm? In this book, Alvin I. Goldman explores these questions with the tools of philosophy, developmental psychology, social psychology and cognitive neuroscience. He refines an approach called simulation theory, which (...) starts from the familiar idea that we understand others by putting ourselves in their mental shoes. Can this intuitive idea be rendered precise in a philosophically respectable manner, without allowing simulation to collapse into theorizing? Given a suitable definition, do empirical results support the notion that minds literally create surrogates of other peoples mental states in the process of mindreading? Goldman amasses a surprising array of evidence from psychology and neuroscience that supports this hypothesis. (shrink)

CHAPTER Simulation theory and mental concepts Alvin I. Goldman Rutgers University. Folk psychology and the TT-ST debate The study of folk psychology, ...

People are minded creatures; we have thoughts, feelings and emotions. More intriguingly, we grasp our own mental states, and conduct the business of ascribing them to ourselves and others without instruction in formal psychology. How do we do this? And what are the dimensions of our grasp of the mental realm? In this book, Alvin I. Goldman explores these questions with the tools of philosophy, developmental psychology, social psychology and cognitive neuroscience. He refines an approach called simulation theory, which (...) starts from the familiar idea that we understand others by putting ourselves in their mental shoes. Can this intuitive idea be rendered precise in a philosophically respectable manner, without allowing simulation to collapse into theorizing? Given a suitable definition, do empirical results support the notion that minds literally create surrogates of other peoples mental states in the process of mindreading? Goldman amasses a surprising array of evidence from psychology and neuroscience that supports this hypothesis. (shrink)

Pierre Jacob (2008) raises several problems for the alleged link between mirroring and mindreading. This response argues that the best mirroring-mindreading thesis would claim that mirror processes cause, rather than constitute, selected acts of mindreading. Second, the best current evidence for mirror-based mindreading is not found in the motoric domain but in the domains of emotion and sensation, where the evidence (ignored by Jacob) is substantial. Finally, simulation theory should distinguish low-level simulation (mirroring) and high-level simulation (involving (...) pretense or imagination). Jacob implies that bi-level simulationism creates an unbridgeable 'gap' in intention reading, but this is not a compelling challenge. (shrink)

Many philosophers and psychologists argue that out everyday ability to predict and explain the actions and mental states of others is grounded in out possession of a primitive 'folk' psychological theory. Recently however, this theory has come under challenge from the simulation alternative. This alternative view says that human beings are able to predict and explain each other's actions by using the resources of their own minds to simulate the psychological aetiology of the actions of the others. This book (...) and the companion volume Folk Psychology: The Theory of Mind Debate together offer a richly woven fabric of philosophical and psychological theory, which promises to yield real insights into the nature of our mental lives. (shrink)

This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, (...) and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text. (shrink)

In this paper, we pursue three general aims: (I) We will define a notion of fundamental opacity and ask whether it can be found in High Energy Physics (HEP), given the involvement of machine learning (ML) and computer simulations (CS) therein. (II) We identify two kinds of non-fundamental, contingent opacity associated with CS and ML in HEP respectively, and ask whether, and if so how, they may be overcome. (III) We address the question of whether any kind of opacity, contingent (...) or fundamental, is unique to ML or CS, or whether they stand in continuity to kinds of opacity associated with other scientific research. (shrink)

The Simulation Theory of Memory states that to remember an episode is to simulate it in the imagination (Michaelian, 2016a, b), making memory thus reducible to the act of imagining. This paper examines Simulation Theory’s resources to account for our ability to distinguish episodic memory from free imagination. The theory suggests that we can reliably do so because of the distinctive phenomenology episodic memory comes with (i.e., a feeling of remembering), which other episodic imaginings lack. I will raise (...) two objections to how the feeling of remembering is engineered in the theory, followed by an exhaustive exploration of the theory’s resources to ground the mechanism underlying the elicitation of such feeling. I will conclude that the Simulation Theory cannot simultaneously defend the simulational character of episodic memory and ground our ability to discriminate between memories and imaginings. (shrink)

This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...) related to the general practice of computer simulations. (shrink)

Baudrillard's bewildering thesis, a bold extrapolation on Ferdinand de Saussure's general theory of general linguistics, is in fact a clinical vision of contemporary consumer societies where signs don't refer anymore to anything except themselves. They all are generated by the matrix. Simulations never existed as a book before it was "translated" into English. Actually it came from two different bookCovers written at different times by Jean Baudrillard. The first part of Simulations, and most provocative because it made a fiction of (...) theory, was "The Procession of Simulacra." It had first been published in Simulacre et Simulations. The second part, written much earlier and in a more academic mode, came from L'Echange Symbolique et la Mort. It was a half-earnest, half-parodical attempt to "historicize" his own conceit by providing it with some kind of genealogy of the three orders of appearance: the Counterfeit attached to the classical period; Production for the industrial era; and Simulation, controlled by the code. It was Baudrillard's version of Foucault's Order of Things and his ironical commentary of the history of truth. The book opens on a quote from Ecclesiastes asserting flatly that "the simulacrum is true." It was certainly true in Baudrillard's book, but otherwise apocryphal.One of the most influential essays of the 20th century, Simulations was put together in 1983 in order to be published as the first little black book of Semiotext's new Foreign Agents Series. Baudrillard's bewildering thesis, a bold extrapolation on Ferdinand de Saussure's general theory of general linguistics, was in fact a clinical vision of contemporary consumer societies where signs don't refer anymore to anything except themselves. They all are generated by the matrix.In effect Baudrillard's essay was upholding the only reality there was in a world that keeps hiding the fact that it has none. Simulacrum is its own pure simulacrum and the simulacrum is true. In his celebrated analysis of Disneyland, Baudrillard demonstrates that its childish imaginary is neither true nor false, it is there to make us believe that the rest of America is real, when in fact America is a Disneyland. It is of the order of the hyper-real and of simulation. Few people at the time realized that Baudrillard's simulacrum itself wasn't a thing, but a "deterrence machine," just like Disneyland, meant to reveal the fact that the real is no longer real and illusion no longer possible. But the more impossible the illusion of reality becomes, the more impossible it is to separate true from false and the real from its artificial resurrection, the more panic-stricken the production of the real is. (shrink)

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

This paper discusses critically what simulation models of the evolution of cooperation can possibly prove by examining Axelrod’s “Evolution of Cooperation” (1984) and the modeling tradition it has inspired. Hardly any of the many simulation models in this tradition have been applicable empirically. Axelrod’s role model suggested a research design that seemingly allowed to draw general conclusions from simulation models even if the mechanisms that drive the simulation could not be identified empirically. But this research design (...) was fundamentally flawed. At best such simulations can claim to prove logical possibilities, i.e. they prove that certain phenomena are possible as the consequence of the modeling assumptions built into the simulation, but not that they are possible or can be expected to occur in reality. I suggest several requirements under which proofs of logical possibilities can nevertheless be considered useful. Sadly, most Axelrod-style simulations do not meet these requirements. It would be better not to use this kind of simulations at all. (shrink)

Experiments are commonly thought to have epistemic privilege over simulations. Two ideas underpin this belief: first, experiments generate greater inferential power than simulations, and second, simulations cannot surprise us the way experiments can. In this article I argue that neither of these claims is true of experiments versus simulations in general. We should give up the common practice of resting in-principle judgments about the epistemic value of cases of scientific inquiry on whether we classify those cases as experiments or simulations, (...) per se. To the extent that either methodology puts researchers in a privileged epistemic position, this is context sensitive. (shrink)

Computer simulation is shown to be philosophically interesting because it introduces a qualitatively new methodology for theory construction in science different from the conventional two components of "theory" and "experiment and/or observation". This component is "experimentation with theoretical models." Two examples from the physical sciences are presented for the purpose of demonstration but it is claimed that the biological and social sciences permit similar theoretical model experiments. Furthermore, computer simulation permits theoretical models for the evolution of physical systems (...) which use cellular automata rather than differential equations as their syntax. The great advantages of the former are indicated. (shrink)

In this volume, scientists, historians, and philosophers join to examine computer simulations in scientific practice. One central aim of the volume is to provide a multiperspective view on the topic. Therefore, the text includes philosophical studies on computer simulations, as well as case studies from simulation practice, and historical studies of the evolution of simulations as a research method.

We review the major phenomena of skilled typing and propose a model for the control of the hands and fingers during typing. The model is based upon an Activation‐Trigger‐Schema system in which a hierarchical structure of schemata directs the selection of the letters to be typed and, then, controls the hand and finger movements by a cooperative, relaxation algorithm. The interactions of the patterns of activation and inhibition among the schemata determine the temporal ordering for launching the keystrokes. To account (...) for the phenomena of doubling errors, the model has only “type” schemata—no “token” schemata—with only a weak binding between the special schema that signals a doubling, and its argument. The model exists as a working computer simulation and produces an output display of the hands and fingers moving over the keyboard. It reproduces some of the major phenomena of typing, including the interkeystroke interval times, the pattern of transposition errors found in skilled typists, and doubling errors. Although the model is clearly inadequate or wrong in some of its features and assumptions, it serves as a useful first approximation for the understanding of skilled typing. (shrink)

Recent application of theories of embodied or grounded cognition to the recognition and interpretation of facial expression of emotion has led to an explosion of research in psychology and the neurosciences. However, despite the accelerating number of reported findings, it remains unclear how the many component processes of emotion and their neural mechanisms actually support embodied simulation. Equally unclear is what triggers the use of embodied simulation versus perceptual or conceptual strategies in determining meaning. The present article integrates (...) behavioral research from social psychology with recent research in neurosciences in order to provide coherence to the extant and future research on this topic. The roles of several of the brain's reward systems, and the amygdala, somatosensory cortices, and motor centers are examined. These are then linked to behavioral and brain research on facial mimicry and eye gaze. Articulation of the mediators and moderators of facial mimicry and gaze are particularly useful in guiding interpretation of relevant findings from neurosciences. Finally, a model of the processing of the smile, the most complex of the facial expressions, is presented as a means to illustrate how to advance the application of theories of embodied cognition in the study of facial expression of emotion. (shrink)

In this chapter I attempt to curb the pretensions of simulationism. I argue that it is, at best, an epistemological doctrine of limited scope. It may explain how we go about attributing beliefs and desires to others, and perhaps to ourselves, in some cases. But simulation cannot provide the fundamental basis of our conception of, or knowledge of, minded agency.

It has been claimed that epistemic peers, upon discovering that they disagree on some issue, should give up their opposing views and ‘split the difference’. The present paper challenges this claim by showing, with the help of computer simulations, that what the rational response to the discovery of peer disagreement is—whether it is sticking to one’s belief or splitting the difference—depends on factors that are contingent and highly context-sensitive.Keywords: Peer disagreement; Computer simulations; Opinion dynamics; Hegselmann–Krause model; Social epistemology.

We simulate trial data to test speculative claims about research methods, such as the impact of publication bias.

I present a new argument that we are much more likely to be living in a computer simulation than in the ground-level of reality. (Similar arguments can be marshalled for the view that we are more likely to be Boltzmann brains than ordinary people, but I focus on the case of simulations.) I explain how this argument overcomes some objections to Bostrom’s classic argument for the same conclusion. I also consider to what extent the argument depends upon an internalist (...) conception of evidence, and I refute the common line of thought that finding many simulations being run—or running them ourselves—must increase the odds that we are in a simulation. GPI Working Paper No. 16-2021. (shrink)

Simulation, if used as a way of becoming aware of other people’s mental states, is the joint exercise of imagination and attribution. If A simulates B, then (i) A attributes to B the mental state in which A finds herself at the end of a process in which (ii) A has imagined being in B’s situation. Although necessary, imagination and attribution are not sufficient for simulation: the latter occurs only if (iii) the imagination process grounds or justifies the (...) attribution. Depending on the notion of justification we use to make sense of the idea that an episode of imagining serves as a reason for attributing a mental state, the shape of the debate and the options it offers look very different. Reconfiguring the discussion in this way, we claim, shifts the focus of the simulation vs. theory-theory debate to a question located in epistemology. (shrink)

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

This paper is concerned with the problem of selfidentification in the domain of action. We claim that this problem can arise not just for the self as object, but also for the self as subject in the ascription of agency. We discuss and evaluate some proposals concerning the mechanisms involved in selfidentification and in agencyascription, and their possible impairments in pathological cases. We argue in favor of a simulation hypothesis that claims that actions, whether overt or covert, are centrally (...) simulated by the neural network, and that this simulation provides the basis for action recognition and attribution. (shrink)

Braun explores the use of digital twin technology in medicine with a particular emphasis on the question of how such simulations can represent a person.1 In defining some first conditions for ethically justifiable forms of representation of digital twins, he argues that digital twins do not threaten an embodied person, as long as that person retains control over their simulated representation via dynamic consent, and ideally with the option to choose both form and usage of the simulation. His thoughtful (...) elaboration provides insight into the challenges inherent in interactions between a person and their digital twin, emphasising the modes of control required to respect personal modes of freedom. This individual-centric approach to the question of representation leaves out the important ethical consideration of ensuring that all, not merely some, can be represented. Braun describes dynamic consent as a necessary mode of control, arguing that where a person is unable to give consent, ‘such simulations threaten to become illegitimate representations. They would then shift the kind of interaction from representation to illegitimate forms of prediction or surveillance and thereby could lead to infringements to individual modes of freedom.’ Consequently, the implementation of digital twin technology in healthcare would seem to exclude the most vulnerable members of society from participation in and benefiting from medical innovation, …. (shrink)

Motor imagery typically involves an experience as of moving a body part. Recent studies reveal close parallels between the constraints on motor imagery and those on actual motor performance. How are these parallels to be explained? We advance a simulative theory of motor imagery, modeled on the idea that we predict and explain the decisions of others by simulating their decision-making processes. By proposing that motor imagery is essentially off-line motor action, we explain the tendency of motor imagery to mimic (...) motor performance. We close by arguing that a simulative theory of motor imagery gives (modest) support to and illumination of the simulative theory of decision-prediction. (shrink)

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

I present arguments against both explicit and implicit versions of the simulation theory for intersubjective understanding. Logical, developmental, and phenomenological evidence counts against the concept of explicit simulation if this is to be understood as the pervasive or default way that we understand others. The concept of implicit (subpersonal) simulation, identified with neural resonance systems (mirror systems or shared representations), fails to be the kind of simulation required by simulation theory, because it fails to explain (...) how neuronal processes meet constraints that involve instrumentality and pretense. Implicit simulation theory also fails to explain how I can attribute a mental or emotion state that is different from my own to another person. I also provide a brief indication of an alternative interpretation of neural resonance systems. (shrink)

Empirical evidence suggests that perceptual‐motor simulations are often constitutively involved in language comprehension. Call this “the simulation view of language comprehension”. This article applies the simulation view to illuminate the much‐discussed phenomenon of copredication, where a noun permits multiple predications which seem to select different senses of the noun simultaneously. On the proposed account, the (in)felicitousness of a copredicational sentence is closely associated with the perceptual simulations that the language user deploys in comprehending the sentence.

This is a penultimate draft of a paper that will appear in Handbook of Imagination, Amy Kind (ed.). Routledge Press. Please cite only the final printed version.

Both Carnap and Quine made significant contributions to the philosophy of mathematics despite their diversed views. Carnap endorsed the dichotomy between analytic and synthetic knowledge and classified certain mathematical questions as internal questions appealing to logic and convention. On the contrary, Quine was opposed to the analytic-synthetic distinction and promoted a holistic view of scientific inquiry. The purpose of this paper is to argue that in light of the recent advancement of experimental mathematics such as Monte Carlo simulations, limiting mathematical (...) inquiry to the domain of logic is unjustified. Robustness studies implemented in Monte Carlo Studies demonstrate that mathematics is on par with other experimental-based sciences. (shrink)

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

This paper describes an operational computer simulation of visual mental imagery in humans. The structure of the simulation was motivated by results of experiments on how people represent information in, and access information from, visual images. The simulation includes a “surface representation,” which is spatial and quasi‐pictorial, and an underlying “deep representation,” which contains “perceptual” information encoding appearance plus “propositional” information describing facts about an object. The simulation embodies a theory of how surface images are generated (...) from deep representations, and how surface images are processed when one accesses information embedded in them. The simulation also offers an account of various sorts of imagery transformations. (shrink)

Preston Greene (2020) argues that we should not conduct simulation investigations because of the risk that we might be terminated if our world is a simulation designed to research various counterfactuals about the world of the simulators. In response, we propose a sequence of arguments, most of which have the form of an "even if” response to anyone unmoved by our previous arguments. It runs thus: (i) if simulation is possible, then simulators are as likely to care (...) about simulating simulations as they are likely to care about simulating basement (i.e. non-simulated) worlds. But (ii) even if simulations are interested only in simulating basement worlds the discovery that we are in a simulation will have little or no impact on the evolution of ordinary events. But (iii) even if discovering that we are in a simulation impacts the evolution of ordinary events, the effects of seeming to do so could also happen in a basement world, and might be the subject of interesting counterfactuals in the basement world Finally, (iv) there is little reason to think that there is a catastrophic effect from successful simulation probes, and no argument from the precautionary principle can be used to leverage the negligible credence one ought have in this. Thus, if we do develop a simulation probe, then let’s do it. (shrink)

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

Mental simulation — such as imagining tilting a glass to figure out the angle at which water would spill — can be a way of coming to know the answer to an internally or externally posed query. Is this form of learning a species of inference or a form of observation? We argue that it is neither: learning through simulation is a genuinely distinct form of learning. On our account, simulation can provide knowledge of the answer to (...) a query even when the basis for that answer is opaque to the learner. Moreover, through repeated simulation, the learner can reduce this opacity, supporting self-training and the acquisition of more accurate models of the world. Simulation is thus an essential part of the story of how creatures like us become effective learners and knowers. (shrink)

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

Par un procédé d'objections/réponses, nous passons d'abord en revue certains des arguments en faveur ou en défaveur du caractère empirique de la simulation informatique. A l'issue de ce chemin clarificateur, nous proposons des arguments en faveur du caractère concret des objets simulés en science, ce qui légitime le fait que l'on parle à leur sujet d'une expérience, plus spécifiquement d'une expérience concrète du second genre.

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

In this article, we provide a case study examining how integrative systems biologists build simulation models in the absence of a theoretical base. Lacking theoretical starting points, integrative systems biology researchers rely cognitively on the model-building process to disentangle and understand complex biochemical systems. They build simulations from the ground up in a nest-like fashion, by pulling together information and techniques from a variety of possible sources and experimenting with different structures in order to discover a stable, robust result. (...) Finally, we analyze the alternative role and meaning theory has in systems biology expressed as canonical template theories like Biochemical Systems Theory. (shrink)

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

Some philosophers regard it as a serious possibility that we now exist within a simulation. That this hypothesis is somewhat probable has been defended extensively by Nick Bostrom. Notably, Bostrom does not defend the conclusion that we inhabit a simulation, but rather the disjunctive conclusion that the human species is very likely to die out before reaching a ‘posthuman stage’, that posthuman civilizations are extremely unlikely to run significant numbers of simulations, or that we almost certainly inhabit a (...) simulation. Bostrom argues that there is no basis for strongly favouring one of these alternatives over its counterparts. The upshot is that it is fairly probable that we inhabit a simulation. I argue that posthuman civilizations are likely to be unwilling to run significant numbers of simulations, thereby undermining the case for assigning a somewhat high probability to the hypothesis that we live in a simulation. (shrink)

This uniquely inspirational and practical book explores human simulation, which is the application of computational modeling and simulation to research subjects in the humanities disciplines. It delves into the fascinating process of collaboration among experts who usually don’t have much to do with one another – computer engineers and humanities scholars – from the perspective of the humanities scholars. It also explains the process of developing models and simulations in these interdisciplinary teams. Each chapter takes the reader on (...) a journey, presenting a specific theory about the human condition, a model of that theory, discussion of its implementation, analysis of its results, and an account of the collaborative experience. Contributing authors with different fields of expertise share how each model was validated, discuss relevant datasets, explain development strategies, and frankly discuss the ups and downs of the process of collaborative development. Readers are given access to the models and will also gain new perspectives from the authors’ findings, experiences, and recommendations. Today we are in the early phases of an information revolution, combining access to vast computing resources, large amounts of human data through social media, and an unprecedented richness of methods and tools to capture, analyze, explore, and test hypotheses and theories of all kinds. Thus, this book’s insights will be valuable not only to students and scholars of humanities subjects, but also to the general reader and researchers from other disciplines who are intrigued by the expansion of the information revolution all the way into the humanities departments of modern universities. (shrink)

: Stich, Nichols et al. assert that the process of deriving predictions by simulation must be cognitively impenetrable. Hence, they claim, the occurrence of certain errors in prediction provides empirical evidence against simulation theory. But it is false that simulation‐derived prediction must be cognitively impenetrable. Moreover the errors they cite, which are instances of irrationality, are not evidence against the version of simulation theory that takes the central domain of simulation to be intelligible transitions between (...) states with content. (shrink)