The paper presents an argument for treating certain types of computer simulation as having the same epistemic status as experimental measurement. While this may seem a rather counterintuitive view it becomes less so when one looks carefully at the role that models play in experimental activity, particularly measurement. I begin by discussing how models function as “measuring instruments” and go on to examine the ways in which simulation can be said to constitute an experimental activity. By focussing on (...) the connections between models and their various functions, simulation and experiment one can begin to see similarities in the practices associated with each type of activity. Establishing the connections between simulation and particular types of modelling strategies and highlighting the ways in which those strategies are essential features of experimentation allows us to clarify the contexts in which we can legitimately call computer simulation a form of experimental measurement. (shrink)

Historically, the hypothesis that our world is a computer simulation has struck many as just another improbable-but-possible “skeptical hypothesis” about the nature of reality. Recently, however, the simulation hypothesis has received significant attention from philosophers, physicists, and the popular press. This is due to the discovery of an epistemic dependency: If we believe that our civilization will one day run many simulations concerning its ancestry, then we should believe that we are probably in an ancestor simulation right (...) now. This essay examines a troubling but underexplored feature of the ancestor-simulation hypothesis: the termination risk posed by both ancestor-simulation technology and experimental probes into whether our world is an ancestor simulation. This essay evaluates the termination risk by using extrapolations from current computing practices and simulation technology. The conclusions, while provisional, have great implications for debates concerning the fundamental nature of reality and the safety of contemporary physics. (shrink)

Simulation Theory says we need not rely exclusively on prepositional knowledge of other minds in order to explain the actions of others. Seeking to know what you will do, I imagine myself in your situation, and see what decision I come up with. I argue that this conception of simulation naturally generalizes: various bits of our mental machine can be run‘off‐line’, fulfilling functions other than those they were made for. In particular, I suggest that visual imagery results when (...) the visual system is run off‐line. I briefly review the empirical evidence and consider the philosophical implications, particularly concerning the mode of mental representation in imagery. (shrink)

Stephen Stich and Shaun Nichols advance the debate over folk psychology with their vivid depiction of the contest between the simulation theory and the theory-theory (Stich & Nichols, this issue). At least two aspects of their presentation I find highly congenial. First, they give a generally fair characterization of the simulation theory, in some respects even improving its formulation. Though I have a few minor quarrels with their formulation, it is mostly quite faithful to the version which I (...) have found attractive (Goldman, 1989).Second, I concur with Stich and Nichols in their assertion that the theory-theory and the simulation theory are the only two games in town. Where I disagree, of course, is in Stich and Nichols’s contention that their arguments so dim the prospects of the simulation theory that it should no longer be taken seriously. On the contrary, I shall maintain, the simulation theory remains a very plausible contender, and should receive careful and respectful consideration in the continuing investigation. (shrink)

This articles develops a taxonomy of memory errors in terms of three conditions: the accuracy of the memory representation, the reliability of the memory process, and the internality (with respect to the remembering subject) of that process. Unlike previous taxonomies, which appeal to retention of information rather than reliability or internality, this taxonomy can accommodate not only misremembering (e.g., the DRM effect), falsidical confabulation, and veridical relearning but also veridical confabulation and falsidical relearning. Moreover, because it does not assume that (...) successful remembering presupposes retention of information, the taxonomy is compatible with recent simulation theories of remembering. (shrink)

Can the theory that reality is a simulation be tested? We investigate this question based on the assumption that if the system performing the simulation is nite (i.e. has limited resources), then to achieve low computational complexity, such a system would, as in a video game, render content (reality) only at the moment that information becomes available for observation by a player and not at the moment of detection by a machine (that would be part of the (...) class='Hi'>simulation and whose detection would also be part of the internal computation performed by the Virtual Reality server before rendering content to the player). Guided by this principle we describe conceptual wave/particle duality experiments aimed at testing the simulation theory. (shrink)

Computer simulations are nowadays often directly involved in the generation of experimental results. Given this dependency of experiments on computer simulations, that of simulations on models, and that of the models on free parameters, how do researchers establish trust in their experimental results? Using high-energy physics (HEP) as a case study, I will identify three different types of robustness that I call conceptual, methodological, and parametric robustness, and show how they can sanction this trust. However, as I will also show, (...) simulation models in HEP themselves fail to exhibit a type of robustness I call inverse parametric robustness. This combination of robustness and failures thereof is best understood by distinguishing different epistemic capacities of simulations and different senses of trust: Trusting simulations in their capacity to facilitate credible experimental results can mean accepting them as means for generating belief in these results, while this need not imply believing the models themselves in their capacity to represent an underlying reality. (shrink)

This paper argues that the key distinguishing feature between simulation and mere resemblance lies in its representational function. Defining this function requires addressing two critical conditions: how neural resemblance denotes its object and how specific content is grounded in such resemblance when it functions as representation. To begin with, the paper posits that the object of simulation is determined by its cognitive role within a broader cognitive system. Second, it examines three potential frameworks for grounding the content of (...) simulation: the Neural Correspondence Thesis (NCT), the Functional Correspondence Thesis (FCT), and the Context-Dependent Correspondence Thesis (CDCT). Both NCT and FCT, the paper shows, encounter problems of content indeterminacy because of their oversimplified assumptions about the relationship between neural activations and mental states. FCT, in particular, faces the issue of over-permissiveness, wherein multiple neural activation patterns correspond to the same mental state, undermining the connection between functional roles and specific content. In response, the paper introduces CDCT as a more robust replacement, addressing both content indeterminacy and over-permissiveness by incorporating context-sensitive mappings between neural states and mental content. Drawing an analogy from the idea of cognitive maps in rats, the paper demonstrates how CDCT clarifies the role of context in shaping the mapping between neural activations and mental content, thereby offering a more precise framework for tackling the complexities of content determination in mental simulations. (shrink)

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. (shrink)

Mindreading (or folk psychology, Theory of Mind, mentalizing) is the capacity to represent and reason about others’ mental states. The Simulation Theory (ST) is one of the main approaches to mindreading. ST draws on the common-sense idea that we represent and reason about others’ mental states by putting ourselves in their shoes. More precisely, we typically arrive at representing others’ mental states by simulating their mental states in our own mind. This entry offers a detailed analysis of ST, considers (...) theoretical arguments and empirical data in favour of and against it, discusses its philosophical implications, and illustrates some alternatives to it. (shrink)

Many philosophical accounts of scientific models fail to distinguish between a simulation model and other forms of models. This failure is unfortunate because there are important differences pertaining to their methodology and epistemology that favor their philosophical understanding. The core claim presented here is that simulation models are rich and complex units of analysis in their own right, that they depart from known forms of scientific models in significant ways, and that a proper understanding of the type of (...) model simulations are fundamental for their philosophical assessment. I argue that simulation models can be distinguished from other forms of models by the many algorithmic structures, representation relations, and new semantic connections involved in their architecture. In this article, I reconstruct a general architecture for a simulation model, one that faithfully captures the complexities involved in most scientific research with computer simulations. Furthermore, I submit that a new methodology capable of conforming such architecture into a fully functional, computationally tractable computer simulation must be in place. I discuss this methodology—what I call recasting—and argue for its philosophical novelty. If these efforts are heading towards the right interpretation of simulation models, then one can show that computer simulations shed new light on the philosophy of science. To illustrate the potential of my interpretation of simulation models, I briefly discuss simulation-based explanations as a novel approach to questions about scientific explanation. (shrink)

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

Are we living in a computer simulation? Some philosophers say it's very likely we are. Some philosophers say that even if we're not in a simulation, we could never know for sure. In this short piece I would like to respond to a more practical question: that is, whatever the case may be, ontologically or epistemically, how do we actually escape (or break) a simulation? I propose a rather simple and sure-fire way to escape a computer (...) class='Hi'>simulation—whether we're in one or not. I also connect my solution to the Fermi Paradox. (shrink)

Morrison points out many similarities between the roles of simulation models and other sorts of models in science. On the basis of these similarities she claims that running a simulation is epistemologically on a par with doing a traditional experiment and that the output of a simulation therefore counts as a measurement. I agree with her premises but reject the inference. The epistemological payoff of a traditional experiment is greater (or less) confidence in the fit between a (...) model and a target system. The source of this payoff is the existence of a causal interaction with the target system. A computer experiment, which does not go beyond the simulation system itself, lacks any such interaction. So computer experiments cannot confer any additional confidence in the fit (or lack thereof) between the simulation model and the target system. (shrink)

Simulation arguments typically presuppose a symmetric hierarchy: an upstream process that enacts a world, and an inhabitant who occupies it, where both levels involve something like an operative standpoint. This paper argues that this symmetry is not structurally required. Drawing on a minimal distinction between compressed and resolved descriptions — a distinction that tracks the functional separability of model and selection roles established by algorithmic information theory — we develop a no-entailment result: support-dependence does not entail upstream resolution. A (...) resolved internal standpoint may depend, as a condition of its reachability, on antecedent support conditions — including, in the simulation case, what would ordinarily be called a simulator — without those conditions themselves constituting any resolved standpoint. The standard picture of simulation as a relation between two resolved levels is therefore a special case rather than a structural requirement. The paper does not adjudicate between competing positions in the simulation literature; it isolates a specific structural assumption that those discussions tend to share and shows that the assumption is not entailed by the support structure that simulation arguments invoke. The general theory of compressed and resolved descriptions on which the argument draws is developed in companion work~\cite{Hitchcock2026CRD}; the present paper is a focused application to simulation arguments specifically. (shrink)

This book presents fresh insights into analogue quantum simulation. It argues that these simulations are a new instrument of science. They require a bespoke philosophical analysis, sensitive to both the similarities to and the differences with conventional scientific practices such as analogical argument, experimentation, and classical simulation. -/- The analysis situates the various forms of analogue quantum simulation on the methodological map of modern science. In doing so, it clarifies the functions that analogue quantum simulation serves (...) in scientific practice. To this end, the authors introduce a number of important terminological distinctions. They establish that analogue quantum ‘computation' and ‘emulation' are distinct scientific practices and lead to distinct forms of scientific understanding. The authors also demonstrate the normative value of the computation vs. emulation distinction at both an epistemic and a pragmatic level. -/- The volume features a range of detailed case studies focusing on: i) cold atom computation of many-body localisation and the Higgs mode; ii) photonic emulation of quantum effects in biological systems; and iii) emulation of Hawking radiation in dispersive optical media. Overall, readers will discover a normative framework to isolate and support the goals of scientists undertaking analogue quantum simulation and emulation. This framework will prove useful to both working scientists and philosophers of science interested in cutting-edge scientific practice. (shrink)

Various theorists contend that we may live in a computer simulation. David Chalmers in turn argues that the simulation hypothesis is a metaphysical hypothesis about the nature of our reality, rather than a sceptical scenario. We use recent work on consciousness to motivate new doubts about both sets of arguments. First, we argue that if either panpsychism or panqualityism is true, then the only way to live in a simulation may be as brains-in-vats, in which case it (...) is unlikely that we live in a simulation. We then argue that if panpsychism or panqualityism is true, then viable simulation hypotheses are substantially sceptical scenarios. We conclude that the nature of consciousness has wide-ranging implications for simulation arguments. (shrink)

This essay investigates the notion of simulation and the role it plays in Kourken Michaelian's simulation theory of memory. I argue that the notion is importantly ambiguous and that this ambiguity may threaten some of the central commitments of the theory. To illustrate that, I examine two different conceptions of simulation: a narrow one (simulation as replication) and a broad one (simulation as computational modeling), arguing that the preferred narrow conception is incompatible with the claim (...) that remembering involves the simulation of past episodes. Investigating possible solutions, I suggest that, despite some relatively serious consequences, the theory may be better off subscribing to the broad notion of simulation. (shrink)

The essays in this volume make it abundantly clear that there is no shortage of disagreement about the plausibility of the simulation theory. As we see it, there are at least three factors contributing to this disagreement. In some instances the issues in dispute are broadly empirical. Different people have different views on which theory is favored by experiments reported in the literature, and different hunches about how future experiments are likely to turn out. In 3.1 and 3.3 we (...) will consider two cases that fall under this heading. With a bit of luck these disputes will be resolved as more experiments are done and more data become available. Faulty arguments are a second source of disagreement. In 3.2 and 3.4 we will set out two dubious arguments advanced by our critics and try to explain exactly why we think they are mistaken. The third source of disagreement is terminological. Terms like "theory-theory," "simulation theory" and a number of others are often not clearly defined, and they are used in different ways by different authors. (Worse yet, we suspect they are sometimes used in different ways by a single author on different occasions). Thus it is sometimes the case that what appears to be a substantive disagreement turns out to be simply a verbal dispute. Moreover, since the labels "theory-theory" and "simulation theory" are each used to characterize a broad range of theories, it may well turn out that some of the theories falling under both headings are correct. In Sections 1 and 2, we will set out a variety of different views for which the labels "theory-theory" and "simulation theory" might be used. As we proceed we'll point out a number of places where disagreements diminish when distinctions among different versions of the theory-theory and the simulation theory are kept clearly in mind. (shrink)

Abstract(Yousefi Heris, Erkenntnis, 2024) offers a version of simulation theory, building on (Goldman, Simulating minds: The philosophy, psychology, and neuroscience of mindreading, Oxford University Press, 2006) and (Herschbach, Synthese 189:483–513, 2012), that refines how to determine the target and content of a simulation. In this critical discussion I will raise some challenges for his account. I first question whether he offers a genuine advance over Herschbach’s account of how to determine the target of a simulation. Then I (...) focus on his account of how to ground the content of simulation. Yousefi Heris surveys three options: the Neural Correspondence Thesis (NCT), the Functional Correspondence Thesis (FCT), and the Context-Dependent Correspondence Thesis (CDCT). He believes only the CDCT can accommodate a modern picture of our brain’s architecture. I disagree with Yousefi Heris’s position that the CDCT is needed to fit with an anti-localizationist picture of the relations between neural states and mental states. Since defending that position would require a paper of its own, I focus on exposing an unacknowledged implication of Yousefi Heris’s account: that it abandons ST’s notions of replication simulation, making it better characterized as a form of the theory theory. (shrink)

This paper describes a novel library implementation for quantum simulation of typical Boolean circuits and several encryption systems. The tool contains half and full adders, binary encoder ($2^{n}$ to $n$), binary decoder ($n$ to $2^{n}$), and multiplexer, as well as its development details accompanied by graphics generated by the software itself. These tools are essential for the implementation of several classical and current ciphers. In addition, studies of optimizations for the quantum paradigm of symmetric encryption systems of different types, (...) such as substitution or permutation ciphers and a simplified version of AES (S-AES), are included. This approach allows a simple and intuitive understanding of the quantum equivalent circuits to the fundamentals of digital electronics and logic design, providing an innovative and pedagogical tool that allows the quantum implementation of classic circuits for real applications including complex encryption systems, starting from previously defined algorithms. (shrink)

No existing account of emotion specifies, in falsifiable terms, which proposed components are strictly necessary rather than merely typical of the human case, leaving human–AI comparisons undecidable. This paper derives a minimal necessary set for emotional emergence and generalizes it into a substrate-neutral evaluative instrument. The Human Emotional Emergence Framework (HEEF) links adaptive pressure, persistent goals, prediction, goal-relevant evaluation, value assignment, action selection, and feedback into one causal chain; four of its seven upstream components, persistent goals, prediction, goal-relevant evaluation, and (...) value assignment, are identified as strictly necessary, with stated falsification conditions. From these necessary conditions the paper derives the Universal Emotional Emergence Framework (UEEF), an eight-component, substrate-neutral instrument applied to humans, animals, and four contemporary large language models using a quantitative scoring rubric. All four models converge on a similar profile: strong satisfaction of prediction-related components and near-total absence of persistent goals and regulatory states, supporting a distinction between emotional simulation (convincing output without underlying architecture) and emotional emergence (the architecture itself). Two reinforcement-learning experiments, a bandit task and a gridworld causal-intervention test, give converging evidence that only architectures whose policy actually reads a carried-over regulatory variable develop cross-episode regulatory behavior. The paper situates HEEF and UEEF against Predictive Processing, Global Workspace Theory, Integrated Information Theory, Active Inference, Appraisal Theory, and Basic Emotion Theory; responds to seven anticipated objections; states falsifiable predictions and the conditions under which each major claim would be disconfirmed; and reports its own limitations directly, including the single-rater status of the AI scoring exercise. (shrink)

According to simulation or shared-substrates models of emotion recognition, our ability to recognize the emotions expressed by other individuals relies, at least in part, on processes that internally simulate the same emotional state in ourselves. The term “emotional expressions” is nearly synonymous, in many people's minds, with facial expressions of emotion. However, vocal prosody and whole-body cues also convey emotional information. What is the relationship between these various channels of emotional communication? We first briefly review simulation models of (...) emotion recognition, and then discuss neuroscientific evidence related to these models, including studies using facial expressions, whole-body cues, and vocal prosody. We conclude by discussing these data in the context of simulation and shared-substrates models of emotion recognition. (shrink)

This article discusses agent-based simulation (ABS) as a tool of sociological understanding. I argue that agent-based simulations can play an important role in the expansion of explanatory understanding in the social sciences. The argument is based on an inferential account of understanding (Ylikoski 2009, Ylikoski & Kuorikoski 2010), according to which computer simulations increase our explanatory understanding by expanding our ability to make what-if inferences about social processes and by making these inferences more reliable. The inferential account also suggests (...) a number of ways in which the use of simulation methodology might give rise to illusory understanding. The structure of the article is as .. (shrink)

This paper draws on the philosophy of Jacques Maritain, a “semiotic Thomist,” to examine lingering issues from the ludology–narratology debate in video game studies. Participants in this debate were explicitly concerned with the compatibility of narrative and play. However, some of their positions anticipated a persistent ambiguity in scholarly accounts of how simulation accomplishes representation. We propose a clarification grounded in Maritain’s Thomistic metaphysics and derived semiotics, arguing that simulation is a highly developed form of representation, not its (...) antithesis. We also articulate what distinguishes video games from other media: they exhibit distinctive representational depth and intimacy. The signified, in terms of its own formal causality, uniquely inheres in the simulative (procedural) sign, while the subjectivity of the player is integrated into the fundament of signification. (shrink)

Simulation theories of social cognition abound in the literature, but it is often unclear what simulation means and how it works. The discovery of mirror neurons, responding both to action execution and observation, suggested an embodied approach to mental simulation. Over the last years this approach has been hotly debated and alternative accounts have been proposed. We discuss these accounts and argue that they fail to capture the uniqueness of embodied simulation (ES). ES theory provides a (...) unitary account of basic social cognition, demonstrating that people e their own mental states or processes represented with a bodily format in functionally attributing them to others. (shrink)

An overview of my work arguing that peer-to-peer computer networking (the Peer-to-Peer Simulation Hypothesis) may be the best explanation of quantum phenomena and a number of perennial philosophical problems.

Nous proposons dans cet article une analyse de l’argument de la Simulation, décrit par Nick Bostrom (2003). Nous décrivons tout d’abord l’argument de la Simulation, en mettant l’accent sur sa structure disjonctive. Nous nous attachons ensuite à compléter l’argument, en restituant plusieurs hypothèses sous-jacentes. Nous ajoutant également à l’argument original plusieurs éléments, dont nous considérons qu’ils constituent autant d’hypothèses pertinentes. Enfin, nous nous attachons à compléter l’argument et en particulier l’arbre de décision qui le sous-tend. Une fois l’argument (...) complété, à l’aide des hypothèses et des éléments de l’arbre de décision manquants, nous en tirons la conclusion, qui est tout à fait différente de celle de l’argument original. (shrink)

Clinical simulation is used in nursing education and in other health professional programs to prepare students for future clinical practice. Simulation can be used to teach students communication skills and how to deliver bad news to patients and families. However, skilled communication in clinical practice requires students to move beyond simply learning superficial communication techniques and behaviors. This article presents an unexplored concept in the simulation literature: the exercise of moral imagination by the health professional student. Drawing (...) from the works of Hume, Aristotle and Gadamer, a conceptualization of moral imagination is first provided. Next, this article argues that students must exercise moral imagination on two levels: towards the direct communication exchange before them; and to the representative nature of simulation encounters. Last, the limits of moral imagination in simulation-based education are discussed. (shrink)

David. J. Chalmers examines eleven possible solutions to the meta-problem of consciousness, ‘the problem of explaining why we think that there is a problem of consciousness.’ The present paper argues that Chalmers overlooks an explanation that he has otherwise taken seriously, and which a number of philosophers, physicists, and computer scientists have taken seriously as well: the hypothesis that we are living in a computer simulation. This paper argues that a particular version of the simulation hypothesis is at (...) least as good of a solution to the meta-problem of consciousness as many explanations Chalmers considers, and may even be a better one—as it may be the best solution to a much broader meta-philosophical problem: the ‘meta-problem of everything’, the problem of explaining why our world has the quantum-mechanical, relativistic, and philosophical features it does. (shrink)

Computer simulations have conventionally been understood to be either extensions of formal methods such as mathematical models or as special cases of empirical practices such as experiments. Here, I argue that computer simulations are best understood as instruments. Understanding them as such can better elucidate their actual role as well as their potential epistemic standing in relation to science and other scientific methods, practices and devices.

The philosophy of AI has a long-standing tradition of discussing brain duplicates and brain simulations as well as a tendency to blur the lines between the two. The distinction between simulating and duplicating the brain has become increasingly important with the emergence of “ʼneuromorphic computers”, hardware operating with bio-inspired mechanisms and interconnecting artificial neurons and synapses. This paper explores what it means to duplicate the brain rather than merely simulate it. I claim that while simulations share only a mathematical structure (...) with their targets, duplicates have the same relevant measurable properties and are governed by the same relevant causal processes as the target system. I propose six criteria for brain duplication that are often not met by simulations, thereby offering a clearer understanding of the complexities involved in achieving brain duplication in artificial systems. Furthermore, this paper explores whether neuromorphic computers can duplicate neural computations by exploring the notion of models of computation. I submit that analog neuromorphic computers that use memristive technology are candidates for duplicating neural structures with respect to simple models of neural computation. Finally, I discuss five possible objections to my view. (shrink)

Mirror neurons and systems are often appealed to as mechanisms enabling mindreading, i.e., understanding other people’s mental states. Such neural mirroring processes are often treated as instances of mental simulation rather than folk psychological theorizing. I will call into question this assumed connection between mirroring and simulation, arguing that mirroring does not necessarily constitute mental simulation as specified by the simulation theory of mindreading. I begin by more precisely characterizing “mirroring” (Sect. 2) and “simulation” (Sect. (...) 3). Mirroring results in a neural process in an observer that resembles a neural process of the same type in the observed agent. Although simulation is often characterized in terms of resemblance (Goldman, Simulating minds: The philosophy, psychology, and neuroscience of mindreading, 2006), I argue that simulation requires more than mere interpersonal mental resemblance: A simulation must have the purpose or function of resembling its target (Sect. 3.1). Given that mirroring processes are generated automatically, I focus on what is required for a simulation to possess the function of resembling its target. In Sect. 3.2 I argue that this resemblance function, at least in the case of simulation-based mindreading, requires that a simulation serve as a representation or stand-in of what it resembles. With this revised account of simulation in hand, in Sect. 4 I show that the mirroring processes do not necessarily possess the representational function required of simulation. To do so I describe an account of goal attribution involving a motor mirroring process that should not be characterized as interpersonal mental simulation. I end in Sect. 5 by defending the conceptual distinction between mirroring and simulation, and discussing the implications of this argument for the kind of neuroscientific evidence required by simulation theory. (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.

Computer simulations are widely used for surrogative reasoning in scientific research. They also play a crucial role in engineering, more specifically in the design of new robotic systems, yet the nature of this role has been little discussed so far in the philosophy of technology literature. The main claim made in this article is that the notion of surrogative reasoning is central to understanding how computer simulations can serve the purpose of designing new robots. More specifically, it is argued that (...) computer simulations can support two forms of surrogative reasoning, which are called model-oriented and prediction-oriented, whose inferential structure is reconstructed to some extent. And it is argued that, when computer simulations are used to design new robots, they are distinctively used in the model-oriented way. By unravelling the structure of the computer simulation-supported methods adopted in robotic design, this article may contribute to a finer-grained understanding of the epistemic processes involved in technological research. (shrink)

The ongoing debate in philosophy of science over whether simulations are experiments has so far operated at too high a level of generality. I revisit this discussion in the context of simulation in astronomy and astrophysics, arguing that a specific subclass of simulations that include a significant amount of empirically obtained temporal data count as experiments. This subclass will be a small one, as the majority of simulations in astronomy and astrophysics will still suffer from a sparseness of data. (...) But it remains the case that there exist examples of simulations that are experiments. (shrink)

Epistemology has recently come to more and more take the articulate form of an investigation into how we do, and perhaps might better, manage the cognitive chores of producing, modifying, and generally maintaining belief-sets with a view to having a true and systematic understanding of the world. While this approach has continuities with earlier philosophy, it admittedly makes a departure from the tradition of epistemology as first philosophy.

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)

In this chapter, we present a transdisciplinary framework where humanities scholars, social scientists, and engineers can work together to tackle large and complex societal problems. We identify the steps required to construct a human simulation model and the concerns and issues that must be addressed to ensure success. We also present some basic definitions and assumptions inherent to developing this sort of model.

This chapter examines the philosophical underpinnings of simulation science, with particular emphasis on the new challenges created by the increased use of computational modelling throughout many disciplines of science. In order to illuminate these philosophical discussions, the discussion here focuses on simulation in the context of Artificial Life – a field which seeks the ‘simulation and synthesis of living systems’.

Towards the end of the 1980s, theory-theory and modularity-theory were accompanied by a rival approach, the simulation-theory, put forward by philosophers Robert Gordon (1986), Jane Heal (1986) and Alvin Goldman (1989) and by developmental psychologist Paul Harris (1992). They reject the idea of a rich body of information needed to understand others. In this chapter, we discuss Alvin Goldman's detailed proposal, according to which we use our own subjective experience as a model to understand what others think and feel. (...) We analyze the notion of mental simulation in some detail and evaluate its application to two distinct levels of mindreading, both of which employ the imagination as a core capacity. Finally, we evaluate theories of embodied simulation which appeal to the mirror neuron system on the implementation level in support of a version of simulation-theory and discuss the contribution of mirror neurons to social understanding more generally. (shrink)