A fundamental aim in caring practice is to understand patients' experiences of ill‐health. These experiences have a qualitative content and cannot, unlike thoughts and beliefs with conceptual content, directly be expressed in words. Nurses therefore face a variety of interpretive challenges when they aim to understand patients' subjective perspectives on disease and illness. The article argues that theories on social simulation can shed light on how nurses manage to meet these challenges. The core assumption of social simulationism (...) is that we do not understand other people by forming mental representations of how they think, but by putting ourselves in their situation in a more imaginative way. According to simulationism, any attempt to understand a patient's behavior is made on the basis of simulating what it is like to be that patient in the given context. The article argues that this approach to social interpretation can clarify how nurses manage to achieve aims of patient understanding, even when they have limited time to communicate and incomplete knowledge of patients' perspectives. Furthermore, simulation theory provides a normative framework for interpretation, in the sense that its theoretical assumptions constitute ideals for how nurses should seek to understand patients' experiences of illness. (shrink)

The article presents social simulation from theoretical and philosophical perspectives as a prognostic tool for researching, analysing and anticipating communication and other processes in social environments. The first part discusses the phenomena of ontological and epistemological simulation, treating social simulation processes as epistemological ones. The second part analyses the attitude of the French sociologist and media philosopher Jean Baudrillard towards social simulation, which he himself treats as ontological one. The counterarguments to introduce (...) Baudrillard’s unidentified distinction between ontological and epistemological simulation processes are presented. The third part deals with the principles of the functioning of social simulations as a prognostic tool and provides analytical possibilities for various social environments, communication and other processes. At the end of the article, it is concluded that Baudrillard’s concept of ontological simulation, which annihilates classical Western metaphysics, erroneously reduces the difference between ontos and epistēmē. (shrink)

This paper tries to answer the question why the epistemic value of so many social simulations is questionable. I consider the epistemic value of a social simulation as questionable if it contributes neither directly nor indirectly to the understanding of empirical reality. To examine this question, two classical social simulations are analyzed with respect to their possible epistemic justification: Schelling’s neighborhood segregation model and Axelrod’s reiterated Prisoner’s Dilemma simulations of the evolution of cooperation. It is argued (...) that Schelling’s simulation is useful because it can be related to empirical reality, while Axelrod’s simulations and those of his followers cannot and thus that their scientific value remains doubtful. I relate this findingto the background beliefs of modelers about the superiority of the modeling method as expressed in Joshua Epstein’s keynote address “Why model?”. (shrink)

Agent-based social simulation (with multi-agent systems), which is an important aspect of social computing, can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents and therefore their social interactions. A cognitive architecture is a domain-generic computational cognitive model that may be used for a broad multiple-domain analysis of individual behavior. In this article, an example of a cognitive architecture is given, and its applications to social simulation described. Some (...) challenging issues in this regard are outlined. (shrink)

ArgumentAgent-based social simulations have historically been evaluated using two criteria: verification and validation. This article questions the adequacy of this dual evaluation scheme. It claims that the scheme does not conform to everyday practices of evaluation, and has, over time, fostered a theory-practice gap in the assessment of social simulations. This gap originates because the dual evaluation scheme, inherited from computer science and software engineering, on one hand, overemphasizes the technical and formal aspects of the implementation process and, (...) on the other hand, misrepresents the connection between the conceptual and the computational model. The mismatch between evaluation theory and practice, it is suggested, might be overcome if practitioners of agent-based social simulation adopt a single criterion evaluation scheme in which: i) the technical/formal issues of the implementation process are tackled as a matter of debugging or instrument calibration, and ii) the epistemological issues surrounding the connection between conceptual and computational models are addressed as a matter of validation. (shrink)

Computational models of group opinion dynamics are one of the most active fields of sociophysics. In recent years, advances in model complexity and, in particular, the possibility to connect these models with detailed data describing individual behaviors, preferences and activities, have opened the way for the simulations to describe quantitatively selected, real world social systems. The simulations could be then used to study ‘what-if’ scenarios for opinion change campaigns, political, ideological or commercial. The possibility of the practical application of (...) the attitude change models necessitates that the research community working in the field should consider more seriously the moral aspects of their efforts, in particular the potential for their use for unintended goals. The paper discusses these issues, and offers a suggestion for a new research direction: using the attitude models to increase the awareness and detection of social manipulation cases. Such research would offer a scientific challenge and meet the ethical criteria. (shrink)

The literature in agent-based social simulation suggests that a model is validated when it is shown to ‘successfully’, ‘adequately’ or ‘satisfactorily’ represent the target phenomenon. The notion of ‘successful’, ‘adequate’ or ‘satisfactory’ representation, however, is both underspecified and difficult to generalise, in part, because practitioners use a multiplicity of criteria to judge representation, some of which are not entirely dependent on the testing of a computational model during validation processes. This article argues that practitioners should address social (...) epistemology to achieve a deeper understanding of how warrants for belief in the adequacy of representation are produced. Two fundamental social processes for validation: interpretation and commensuration, are discussed to justify this claim. The analysis is advanced with a twofold aim. First, it shows that the conceptualisation of validation could greatly benefit from incorporating elements of social epistemology, for the criteria used to judge adequacy of representation are influenced by the social, cognitive and physical organisation of social simulation. Second, it evidences that standardisation tools such as protocols and frameworks fall short in accounting for key elements of social epistemology that affect different instances of validation processes. (shrink)

We consider here issues of open access to social simulations, with a particular focus on software licences, though also briefly discussing documentation and archiving. Without any specific software licence, the default arrangements are stipulated by the Berne Convention (for those countries adopting it), and are unsuitable for software to be used as part of the scientific process (i.e. simulation software used to generate conclusions that are to be considered part of the scientific domain of discourse). Without stipulating any (...) specific software licence, we suggest rights that should be provided by any candidate licence for social simulation software, and provide in an appendix an evaluation of some popularly used licences against these criteria. (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)

This special issue on social simulation presents a collection of selected papers from the 5th conference of the European Social Simulation Association held in Brescia, Italy 1st to 5th September 2008. This collection includes multi-faceted research from this trans-disciplinary community that revolves around social simulation.

Some issues and varieties of computational and other approaches to understanding socially embedded phenomena are discussed. It is argued that of all the approaches currently available, only agent-based simulation holds out the prospect for adequately representing and understanding phenomena such as social norms.

It is widely recognized that the Web contributes to user polarization, and such polarization affects not just politics but also peoples’ stances about public health, such as vaccination. Understanding polarization in social networks is challenging because it depends not only on user attitudes but also their interactions and exposure to information. We adopt Social Judgment Theory to operationalize attitude shift and model user behavior based on empirical evidence from past studies. We design a social simulation to (...) analyze how content sharing affects user satisfaction and polarization in a social network. We investigate the influence of varying tolerance in users and selectively exposing users to congenial views. We find that (1) higher user tolerance slows down polarization and leads to lower user satisfaction; (2) higher selective exposure leads to higher polarization and lower user reach; and (3) both higher tolerance and higher selective exposure lead to a more homophilic social network. (shrink)

This is an excerpt from the contentThe European Social Simulation Association was founded in 2002 by a scientific coalition, the SimSoc consortium, active ever since the first years of social simulation . Ten years before, the first of a series of SimSoc symposia held in Surrey in 1992, marked the birth of a new scientific field, the computer simulation of social life. The volume from the 2nd SimSoc symposium, published in 1995, was titled Artificial (...) Societies . The next year, in 1996, came out the best-seller by Epstein and Axtell Growing Artificial Societies.The planetary dimension of social simulation became apparent through the number of scientific events spreading throughout the world, favoured by increasing synergies both within the social scientific disciplines and across major scientific areas. To computer simulation turned anthropologists, ethologists, geographers, but also computer scientists and ICT designers, ecologists. (shrink)

The focus of social simulation on representing the social world calls for an investigation of whether its implementations are inherently value-laden. In this article, I investigate what kind of thing implementation is in social simulation and consider the extent to which it has moral significance. When the purpose of a computational artefact is simulating human institutions, designers with different value judgements may have rational reasons for developing different implementations. I provide three arguments to show that (...) different implementations amount to taking moral stands via the artefact. First, the meaning of a social simulation is not homogeneous among its users, which indicates that simulations have high interpretive malleability. I place malleability as the condition of simulation to be a metaphorical vehicle for representing the social world, allowing for different value judgements about the institutional world that the artefact is expected to simulate. Second, simulating the social world involves distinguishing between malfunction of the artefact and representation gaps, which reflect the role of meaning in simulating the social world and how meaning may or not remain coherent among the models that constitute a single implementation. Third, social simulations are akin to Kroes’ techno-symbolic artefacts, in which the artefact’s effectiveness relative to a purpose hinges not only on the functional effectiveness of the artefact’s structure, but also on the artefact’s meaning. Meaning, not just technical function, makes implementations morally appraisable relative to a purpose. I investigate Schelling’s model of ethnic residential segregation as an example, in which different implementations amount to taking different moral stands via the artefact. (shrink)

During the COVID-19 crisis there have been many difficult decisions governments and other decision makers had to make. E.g. do we go for a total lock down or keep schools open? How many people and which people should be tested? Although there are many good models from e.g. epidemiologists on the spread of the virus under certain conditions, these models do not directly translate into the interventions that can be taken by government. Neither can these models contribute to understand the (...) economic and/or social consequences of the interventions. However, effective and sustainable solutions need to take into account this combination of factors. In this paper, we propose an agent-based social simulation tool, ASSOCC, that supports decision makers understand possible consequences of policy interventions, but exploring the combined social, health and economic consequences of these interventions. (shrink)

Finding suitable analysis techniques for networks generated from social processes is a difficult task when the population changes over time. Traditional social network analysis measures may not work in such circumstances. It is argued that agent-based social networks should not be constrained by a priori assumptions about the evolved network and/or the analysis techniques. In most agent-based social simulation models, the number of agents remains fixed throughout the simulation; this paper considers the case when (...) this does not hold. Thus the aim of this paper is to demonstrate how the network signatures change when the agents’ population depends upon endogenous social processes. We argue for a much wider attention from the social simulation community in addressing this open research problem. (shrink)

As we know, a cognitive architecture is a domain-generic computational cognitive model that may be used for a broad analysis of cognition and behavior. Cognitive architectures embody theories of cognition in computer algorithms and programs. Social simulation with multi-agent systems can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents (as argued in Sun 2001). In this survey, an example cognitive architecture will be given, and its application to social simulation (...) will be sketched. (shrink)

Although computational models of cognitive agents that incorporate a wide range of cognitive functionalities have been developed in cognitive science, most of the work in social simulation still assumes rudimentary cognition on the part of the agents. In contrast, in this work, the interaction of cognition and social structures/processes is explored, through simulating survival strategies of tribal societies. The results of the simulation demonstrate interactions between cognitive and social factors. For example, we show that cognitive (...) capabilities and tendencies may be relevant to what social institutions may be adopted. This work points to a cognitively based approach towards social simulation, as well as a new area of research—exploring the cognitive–social interaction through cognitively based social simulation. (shrink)

A program for the simulation of rational social normative trust, predictive `trust,' and predictive reliance between agents will be introduced. It offers a tool for social scientists or a trust component for multi-agent simulations/multi-agent systems, which need to include trust between agents to guide the decisions about the course of action. It is based on an analysis of rational social normative trust (RSNTR) (revised version of M. Tuomela 2002), which is presented and briefly argued. For collective (...) agents, belief conditions for collective agency should be added. For the various forms of trust agents must have (at least) subjectively rational reasons to believe that the conditions of the trust account are fulfilled. A list of such reasons (of varied weights), e.g., given by empirical research, can manually be built into a parameter file or be generated by a calling program in a fixed format. From this list of reasons the program randomly generates a belief base for the agents of the artificial society. Reasons can be chained together so that one set of reasons satisfies several belief conditions. The program checks if the conditions are fulfilled for the artificial agents' social normative trust/predictive `trust'/`predictive reliance' in another agent that he will perform an action X. Each outcome is logged to a result file. In conclusion we discuss various aspects of the application of a trust component of the suggested kind in empirical research, social simulation, and multi-agent systems. (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)

Citizen event reporting (CER) attempts to leverage the eyes and ears of a large population of citizen sensors to increase the amount of information available to decision makers. When deployed in an environment that includes hostile elements, foes can exploit the system to exert indirect control over the response infrastructure. We use an agent-based model to relate the utility of responses to population composition, citizen behavior, and decision strategy, and measure the result in terms of a force multiplier. We show (...) that CER can lead to positive force multipliers even with a majority of hostile elements in the population. When reporter identity is known, a reputation system that keeps track of trustworthy reporters can further increase the force multipliers. (shrink)

Les modèles basés sur des agents en interactions, constituent des systèmes sociaux complexes, qui peuvent être simulés par informatiques. Ils se répandent dans les sciences économiques et sociales - comme dans la plupart des sciences des systèmes complexes. Des énigmes épistémologiques (ré)apparaissent. On a souvent opposé modèles et investigations empiriques : d’un côté, on considère les sciences empiriques fondées sur une observation méthodique (enquêtes, expériences) tandis que de l’autre, on conçoit les approches théoriques et la modélisation comme s’appuyant sur une (...) approche conceptuelle ou hypothético-déductive. la simulation a de son coté souvent été comparée à une forme d’expérience ou à une méthode intermédiaire entre la théorie et l’expérience. Tesfatsion a parlé de « laboratoire computationnel » comme d’une manière d’étudier « les comportements des systèmes complexes au moyen d’expériences sous contrôle qu’on peut répéter (réplicable)» et Axelrod a proclamé que la simulation serait « une troisième manière de pratiquer la science dans les sciences sociales », entre l’induction et la déduction. Nous introduisons de nouveaux concepts épistémologiques afin de montrer dans quelle mesure les auteurs ont raison lorsqu'ils se concentrent sur une signification empirique, instrumentale ou conceptuelle de leur modèle ou simulation. La première partie du chapitre discute plus particulièrement de l'épistémologie des modèles économiques à partir des travaux d’Hausman, Guala, Mäki, Sugden, Schelling etc. pour expliquer les divergences entre modèles et simulations. En distinguant entre modèles et simulations, comme entre entre types de modèles, types de simulations informatiques et types d'empiricité obtenue par une simulation, la seconde partie donne la possibilité de comprendre plus précisément - et ensuite de justifier - la diversité des positions épistémologiques présentées dans la première partie. En utilisant les notion de sous-symbolisation (due à Smolensky) et, de hiérarchie dénotationnelle (due à Goodman), une attention particulière est accordée à la multiplicité des pouvoirs dénotationnels des symboles en jeu dans les modèles complexes et les simulations informatiques. Selon cette grille d'analyse, on peut déterminer, dans chaque cas particulier son statut épistémique et la crédibilité qui peut y être associée. -/- Ce chapitre est une traduction (par Gilles Campagnolo) réviséee et augmentée par les auteurs de : Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting, Journal of Artificial Societies and Social Simulation 13 (1) 5 DOI: 10.18564/jasss.1532. (shrink)

This volume brings together contributions from leading researchers in the field of agent-based modelling and simulation. This approach has grown out of some recent and innovative ideas in the social sciences, computer sciences, life sciences, physics and game theory. It is proving helpful in understanding complexity in many domains. The opportunities it offers to explore the experimental approach to social and human behaviour is proving of theoretical and empirical value across a wide range of fields. With contributions (...) from researchers whose work has served to define this new field such as Nigel Gilbert, Robert Axtell (in economics and social science) and Jacques Ferber (in multi-agent systems), as well as practitioners who are working at the cutting edge of the new domain, this collection of essays has been assembled by two of its leading exponents: Frédéric Amblard and Denis Phan. The research, case studies and theoretical approaches discussed in this book are designed to introduce beginners and experts alike to the current state of play in this new and exciting field of social science. (shrink)

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

In a seminal book, Alvin I. Goldman outlines a theory for how to evaluate social practices with respect to their “veritistic value”, i.e., their tendency to promote the acquisition of true beliefs in society. In the same work, Goldman raises a number of serious worries for his account. Two of them concern the possibility of determining the veritistic value of a practice in a concrete case because we often don't know what beliefs are actually true, and even if we (...) did, the task of determining the veritistic value would be computationally extremely difficult. Neither problem is specific to Goldman's theory and both can be expected to arise for just about any account of veritistic value. It is argued here that the first problem does not pose a serious threat to large classes of interesting practices. The bulk of the paper is devoted to the computational problem, which, it is submitted, can be addressed in promising terms by means of computer simulation. In an attempt to add vividness to this proposal, an up-and-running simulation environment is presented and put to some preliminary tests. (shrink)

The mechanism by which humans perceive others differs greatly from how humans perceive inanimate objects. Unlike inanimate objects, humans have the distinct property of being “like me” in the eyes of the observer. This allows us to use the same systems that process knowledge about self-performed actions, self-conceived thoughts, and self-experienced emotions to understand actions, thoughts, and emotions in others. The authors propose that internal simulation mechanisms, such as the mirror neuron system, are necessary for normal development of recognition, (...) imitation, theory of mind, empathy, and language. Additionally, the authors suggest that dysfunctional simulation mechanisms may underlie the social and communicative deficits seen in individuals with autism spectrum disorders. (shrink)

In a seminal book, Alvin I. Goldman outlines a theory for how to evaluate social practices with respect to their , i.e., their tendency to promote the acquisition of true beliefs (and impede the acquisition of false beliefs) in society. In the same work, Goldman raises a number of serious worries for his account. Two of them concern the possibility of determining the veritistic value of a practice in a concrete case because (1) we often don't know what beliefs (...) are actually true, and (2) even if we did, the task of determining the veritistic value would be computationally extremely difficult. Neither problem is specific to Goldman's theory and both can be expected to arise for just about any account of veritistic value. It is argued here that the first problem does not pose a serious threat to large classes of interesting practices. The bulk of the paper is devoted to the computational problem, which, it is submitted, can be addressed in promising terms by means of computer simulation. In an attempt to add vividness to this proposal, an up-and-running simulation environment (Laputa) is presented and put to some preliminary tests. (shrink)

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

The social sciences and humanities are fragmented into specialized areas, each with their own parlance and procedures. This hinders information sharing and the growth of a coherent body of knowledge. Modeling and simulation can be the scientific lingua franca, or shared technical language, that can unite, integrate, and relate relevant parts of these diverse disciplines.Models are well established in the scientific community as mediators, contributors, and enablers of scientific knowledge. We propose a potentially revolutionary linkage between social (...) sciences, humanities and computer simulation, forging what we call “human simulation.” We explore three facets of human simulation, namely: the simulation of humans, the design of simulations for human use, and simulations that include humans as well as simulated agents among the actors. We describe the potential of human simulation using several illuminating examples. We also discuss computational, epistemological, and hermeneutical challenges constraining the use of human simulation. (shrink)

Genetic Programming (GP) is a technique which permits automatic search for complex solutions using a computer. It goes beyond previous techniques in that it discovers the structure of those solutions. Previously, if one were trying to find an equation to fit a set of data, one would have had to provide the form of the equation (for example a fourth degree polynomial) and the computer could then find the appropriate parameters. By contrast, GP can experiment with a whole range of (...) different functional forms , building equations from a menu of functions, symbols and arithmetic operations. Thus GP can be seen as an essentially creative technique. It is good at finding novel solutions where not much is known about the form of the solution.. (shrink)

I explore a type of computational social simulation known as artificial societies. Artificial society simulations are dynamic models of real-world social phenomena. I explore the role that these simulations play in social explanation, by situating these simulations within contemporary philosophical work on explanation and on models. Many contemporary philosophers have argued that models provide causal explanations in science, and that models are necessary mediators between theory and data. I argue that artificial society simulations provide causal mechanistic (...) explanations. I conclude that in their current form, these simulations are based on methodologically individualist assumptions that could limit their potential scope of social explanation. (shrink)

At least since Kuhn’s Structure, philosophers have studied the influence of social factors in science’s pursuit of truth and knowledge. More recently, formal models and computer simulations have allowed philosophers of science and social epistemologists to dig deeper into the detailed dynamics of scientific research and experimentation, and to develop very seemingly realistic models of the social organization of science. These models purport to be predictive of the optimal allocations of factors, such as diversity of methods used (...) in science, size of groups, and communication channels among researchers. In this paper we argue that the current research faces an empirical challenge. The challenge is to connect simulation models with data. We present possible scenarios about how the challenge may unfold. (shrink)

Interactions of entrepreneurs through social networks provide an available path for corporate risk contagions. However, the issue how entrepreneurs’ social networks influence on corporate risk contagion is still received limited attention from scholars. In this study, a framework is proposed to describe entrepreneurs’ interaction and corporate value creation. The main results of multiagent simulations indicate the following. First, either weak ties or strong connections of social networks can enhance density of corporate risk contagion. However, only strong connections (...) can be moderated by entrepreneurs’ risk preference. Second, weak ties improve risk exposure of individual corporations, while strong connections may probably decrease systematical risk of the market. Third, weak ties are important for mature corporations to achieve business success. However, for startups, strong connections are more valuable to maintain. The findings of this study not only provide theoretical support from some widely accepted economic phenomenon but also provide explanations for conflicting results from some previous literatures. (shrink)

From a sociological perspective, Rational Choice Theory neglects an important question: How do agents come to conceptualise choices as they do? In particular, agents not only communicate about their choices and resulting outcomes but also draw attention to options unconsidered by others. This paper presents an agent-based simulation in which different kinds of information about choices are transmitted. This approach also provides a concrete model for certain aspects of hegemonic discourse . In standard Rational Choice where options are common (...) knowledge, all actors with the same preferences should make the same decisions. By contrast if information is transmitted socially, the concerns of a majority may reduce the ability of a minority to choose options appropriate to them even without any exercise of coercion or discrimination. (shrink)

Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological concepts so as to show to what extent authors are right when they focus on some empirical, instrumental or conceptual significance of their model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity obtained through a (...) simulation, section 2 gives the possibility to understand more precisely - and then to justify - the diversity of the epistemological positions presented in section 1. Our final claim is that careful attention to the multiplicity of the denotational powers of symbols at stake in complex models and computer simulations is necessary to determine, in each case, their proper epistemic status and credibility. (shrink)

In their article, Cho and Martinez-Martin (2023) argue that developers and users of digital simulacra for modelling health and disease should involve a continued focus on causality of health states...

Shaun Gallagher and Dan Zahavi have recently argued against a simulationist interpretation of neural resonance. Recognizing intentions and emotions in the facial expressions and gestures of others may be subserved by e.g. mirror neuron activity, but this does not mean that we first experience an intention or emotion and then project it onto the other. Mirror neurons subserve social cognition, according to Gallagher and Zahavi, by being integral parts of processes of enactive social perception. I argue that the (...) notion of enactive social perception does not yet explain why social perception is subserved by mirroring. I also argue that this problem cannot be avoided by means of an appeal to multiple realization. Instead, I propose a holistic model of neural resonance-based social cognition that does give an explanatory role to mirroring by allowing for a partial experiential overlap between experiencing and recognizing emotions and intentions. This account avoids the simulationist step-wise conception of social cognition and recognizes the qualitative difference between first- and third-person emotion and intention attribution. It does capture too much of the simulationist intuitions, however, to warrant the label ‘social perception’. (shrink)

The justification of induction is of central significance for cross-cultural social epistemology. Different ‘epistemological cultures’ do not only differ in their beliefs, but also in their belief-forming methods and evaluation standards. For an objective comparison of different methods and standards, one needs (meta-)induction over past successes. A notorious obstacle to the problem of justifying induction lies in the fact that the success of object-inductive prediction methods (i.e., methods applied at the level of events) can neither be shown to be (...) universally reliable (Hume's insight) nor to be universally optimal. My proposal towards a solution of the problem of induction is meta-induction. The meta-inductivist applies the principle of induction to all competing prediction methods that are accessible to her. By means of mathematical analysis and computer simulations of prediction games I show that there exist meta-inductive prediction strategies whose success is universally optimal among all accessible prediction strategies, modulo a small short-run loss. The proposed justification of meta-induction is mathematically analytical. It implies, however, an a posteriori justification of object-induction based on the experiences in our world. In the final section I draw conclusions about the significance of meta-induction for the social spread of knowledge and the cultural evolution of cognition, and I relate my results to other simulation results which utilize meta-inductive learning mechanisms. (shrink)