The explosive growth in computational power over the past several decades offers new tools and opportunities for economists. This handbook volume surveys recent research on Agent-based Computational Economics (ACE), the computational study of economic processes modeled as open-ended dynamic systems of interacting agents. Empirical referents for “agents” in ACE models can range from individuals or social groups with learning capabilities to physical world features with no cognitive function. Topics covered include: learning; empirical validation; network economics; social dynamics; financial markets; innovation (...) and technological change; organizations; market design; automated markets and trading agents; political economy; social-ecological systems; computational laboratory development; and general methodological issues. (shrink)

Agent-based modelling has become a well-established method in social epistemology and philosophy of science but the question of what kind of explanations these models provide remains largely open. This paper is dedicated to this issue. It starts by distinguishing between real-world phenomena, real-world possibilities, and logical possibilities as different kinds of targets which agent-based models can represent. I argue that models representing the former two kinds provide how-actually explanations or causal how-possibly explanations. In contrast, models that represent logical possibilities provide (...) epistemically opaque how-possibly explanations. While highly idealised ABMs in the form in which they are initially proposed typically fall into the last category, the epistemic opaqueness of explanations they provide can be reduced by validation procedures. To this purpose, an examination of results of simulations in terms of classes of models can be particularly helpful. I illustrate this point by discussing a class of ABMs of scientific interaction and the claim that a high degree of interaction can impede scientific inquiry. (shrink)

Throughout most of the 20th century, analytical and reductionist approaches have dominated in biological, social, and humanistic sciences, including linguistics and communication. We generally believed we could account for fundamental phenomena in invoking basic elemental units. Although the amount of knowledge generated was certainly impressive, we have also seen limitations of this approach. Discovering the sound formants of human languages, for example, has allowed us to know vital aspects of the ‘material’ plane of verbal codes, but it tells us little (...) about significant aspects of their social functions. I firmly believe, therefore, that alongside a linguistics that looks ‘inward’ there should also be a linguistics that looks ‘outward’, or one even that is constructed ‘from the outside’, a linguistics that I refer to elsewhere as ‘holistic’ though it could be identified by a different name. My current vision is to promote simultaneously the perspective that goes from the part to the whole and that which goes from the whole to the parts, i.e., both from the top down and from the bottom up. This goal is shared with other disciplines which recognize that many phenomena related to life are interwoven, self-organising, emergent and processual. Thus, we need to re-examine how we have conceived of reality, both the way we have looked at it and the images we have used to talk about it. Several approaches now grouped under the label of complexity have been elaborated towards this objective of finding new concepts and ways of thinking that better fit the complex organisation of facts and events. (shrink)

Scientists and engineers seek to understand how real-world systems work and could work better. Any modeling method devised for such purposes must simplify reality. Ideally, however, the modeling method should be flexible as well as logically rigorous; it should permit model simplifications to be appropriately tailored for the specific purpose at hand. Flexibility and logical rigor have been the two key goals motivating the development of Agent-based Computational Economics (ACE), a completely agent-based modeling method characterized by seven specific modeling principles. (...) This perspective provides an overview of ACE, a brief history of its development, and its role within a broader spectrum of experiment-based modeling methods. (shrink)

This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; (...) and cutting-edge developments in techniques to achieve AI, including machine learning, neural networks, dynamical systems. The book also discusses important applications of AI, including big data analytics, expert systems, cognitive architectures, and robotics. It offers a timely, yet very comprehensive snapshot of what is going on in the field of AI, especially at the interfaces between philosophy, cognitive science, ethics and computing. (shrink)

Complex systems are to be seen as typically having multiple levels of organization. For instance, in the behavioural and cognitive sciences, there has been a long lasting trend, promoted by the seminal work of David Marr, putting focus on three distinct levels of analysis: the computational level, accounting for the What and Why issues, the algorithmic and the implementational levels specifying the How problem. However, the tremendous developments in neuroscience knowledge about processes at different scales of organization together with the (...) complexity of today cognitive theories suggest that there will hardly be only three levels of explanation. Instead, there will be many different degrees of commitments corresponding to the different granularities—from high-level (behavioural) models to low-level (neural and molecular) models of the cognitive research program. For instance, Bayesian approaches, that are usually advocated for formalizing Marr’s computational level and rational behaviour, have even been adopted to model synaptic plasticity and axon guidance by molecular gradients. As a result, we can consider the behavioural scientist as dealing with models at a multiplicity of levels. The purpose of this Research Topic in Frontiers in Theoretical and Philosophical Psychology is to promote an approach to the role of the levels and explanation and models which is of interest for cognitive scientists, neuroscientists, psychologists, behavioural scientists, and philosophers of science. (shrink)

Proponents of individual-based modeling in ecology claim that their models explain the emergence of population-level behavior. This article argues that individual-based models have not, as yet, provided such explanations. Instead, individual-based models can and do demonstrate and explain the emergence of population-level behaviors from individual behaviors and interactions.

In this article, I examine Luhmann’s, Bunge’s and others’ views on emergence, and argue that Luhmann’s epistemological construal of emergence in terms of Totalausschluss (total exclusion) is both ontologically flawed and detrimental to an appropriate understanding of the distinctive features of social emergence. By contrast, Bunge’s rational emergentism, his CESM model, and Wimsatt’s characterization of emergence as nonaggregativity provide a useful framework to investigate emergence. While researchers in the field of social theory and sociology tend to regard Luhmann as the (...) sole representative of systems theory, the latter has been characterized by its diversity, and the writings of such systems theorists as Mario Bunge deserve more (critical) attention from social researchers than they receive at present. Finally, this article suggests that the perennial debate over methodological individualism and holism in social science may make real progress if such ambiguous terms as reduction and reductionism are elucidated before they are employed. (shrink)

Computation and Simulation have always played a role in economics – whether it be pure economic theory or any variant of applied, especially policy-oriented, macro- and microeconomics or what has increasingly come to be called empirical or experimental economics. Computations and simulations are also intrinsically dynamic. This triptych – computation, simulation and dynamic – is given natural foundations, mainly as a result of developments in the mathematics underpinnings in the potentials of computing, using digital technology. A running theme in this (...) essay is the recognition that, increasingly, the development of economic theory seems to go hand in hand with advances in the theory and practice of computing, which is, in turn, a catalyst for the move away from too much reliance on any kind of mathematics for the formalisation of economic entities that is inconsistent with the mathematical, methodological and epistemological foundations of the theory of computation. (shrink)

The proliferation of digital data has been the impetus for the emergence of a new discipline for the study of social life: ‘computational social science’. Much research in this field is founded on the premise that society is a complex system with emergent structures that can be modeled or reconstructed through digital data. This paper suggests that computational social science serves practical and legitimizing functions for digital capitalism in much the same way that neoclassical economics does for neoliberalism. In recognition (...) of this homology, this paper develops a critique of the complexity perspective of computational social science and argues for a heterodox computational social science founded on the meta-theory of critical realism that is critical, methodological pluralist, interpretative and explanative. This implies diverting computational social science’ computational methods and digital data so as to not be aimed at identifying invariant laws of social life, or optimizing state and corporate practices, but to instead be used as part of broader research strategies to identify contingent patterns, develop conjunctural explanations, and propose qualitatively different ways of organizing social life. (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.

Public discussions of political and social issues are often characterized by deep and persistent polarization. In social psychology, it’s standard to treat belief polarization as the product of epistemic irrationality. In contrast, we argue that the persistent disagreement that grounds political and social polarization can be produced by epistemically rational agents, when those agents have limited cognitive resources. Using an agent-based model of group deliberation, we show that groups of deliberating agents using coherence-based strategies for managing their limited resources tend (...) to polarize into different subgroups. We argue that using that strategy is epistemically rational for limited agents. So even though group polarization looks like it must be the product of human irrationality, polarization can be the result of fully rational deliberation with natural human limitations. (shrink)

This article explores some of the ways in which the conceptual apparatus of A Thousand Plateaus, and especially its machinic metaphysics, can be connected to recent developments in computer modelling and social simulation, which provide new tools for thinking that are becoming increasingly popular among philosophers and social scientists. Conversely, the successful deployment of these tools provides warrant for the flat ontology articulated in A Thousand Plateaus and therefore contributes to the ‘reversal of Platonism’ for which Deleuze had called in (...) his earlier works, such as Logic of Sense. The first major section offers a brief exposition of some key concepts in A Thousand Plateaus in order to set the stage for the second and third major sections, which argue that the fabrication of a metaphysics of immanence can be accelerated by connecting its conceptual apparatus more explicitly to insights derived from philosophical analyses of computational modelling and simulation and the social scientific use of ‘assemblage theory’. The article concludes with a summary of the argument and a brief consideration of some of the potential ethical and political implications of this interdisciplinary engagement. (shrink)

For the last three decades, physicists have been moving beyond the boundaries of their discipline, using their methods to study various problems usually instigated by economists. This trend labeled ‘econophysics’ can be seen as a hybrid area of knowledge that exists between economics and physics. Econophysics did not spring from nowhere—the existing literature agrees that econophysics emerged in the 1990s and historical studies on the field mainly deal with what happened during that decade. This article aims at investigating what happened (...) before the 1990s by clarifying the epistemic background that might have paved the way to the emergence of econophysics. This historical exploration led me to highlight the active role played by the Santa Fe Institute by promoting interdisciplinary research on complexity in 1980s. Precisely, by defining three research themes on economic complexity, the SFI defined a research agenda and a way of extending physics\biology to economics. This article offers a possible archeology of econophysics to clarify what could have contributed to the development of a particular episteme in the 1980s easing the advent of econophysics in the 1990s. (shrink)

Computational sociology models social phenomena using the concepts of emergence and downward causation. However, the theoretical status of these concepts is ambiguous; they suppose too much ontology and are invoked by two opposed sociological interpretations of social reality: the individualistic and the holistic. This paper aims to clarify those concepts and argue in favour of their heuristic value for social simulation. It does so by proposing a link between the concept of emergence and Luhmann's theory of communication. For Luhmann, society (...) emerges from the bottom-up as communication and he describes the process by which society limits the possible selections of individuals as downward causation. It is argued that this theory is well positioned to overcome some epistemological drawbacks in computational sociology. (shrink)

In this paper I look at causality in the context of intervention research, and discuss some problems faced in the evaluation of causal hypotheses via interventions. I draw attention to a simple problem for evaluations that employ randomized controlled trials. The common alternative to randomized trials, the observational study, is shown to face problems of a similar nature. I then argue that these problems become especially acute in cases where the intervention is complex (i.e. that involves intervening in a complex (...) system). Finally, I consider and reject a possible resolution of the problem involving the simulation of complex interventions. The conclusion I draw from this is that we need to radically reframe the way we think about causal inference in complex intervention research. (shrink)

The understanding of decision-making systems has come together in recent years to form a unified theory of decision-making in the mammalian brain as arising from multiple, interacting systems (a planning system, a habit system, and a situation-recognition system). This unified decision-making system has multiple potential access points through which it can be driven to make maladaptive choices, particularly choices that entail seeking of certain drugs or behaviors. We identify 10 key vulnerabilities in the system: (1) moving away from homeostasis, (2) (...) changing allostatic set points, (3) euphorigenic signals, (4) overvaluation in the planning system, (5) incorrect search of situation-action-outcome relationships, (6) misclassification of situations, (7) overvaluation in the habit system, (8) a mismatch in the balance of the two decision systems, (9) over-fast discounting processes, and (10) changed learning rates. These vulnerabilities provide a taxonomy of potential problems with decision-making systems. Although each vulnerability can drive an agent to return to the addictive choice, each vulnerability also implies a characteristic symptomology. Different drugs, different behaviors, and different individuals are likely to access different vulnerabilities. This has implications for an individual's susceptibility to addiction and the transition to addiction, for the potential for relapse, and for the potential for treatment. (shrink)

Epidemiological models have played a central role in the COVID-19 pandemic, particularly when urgent decisions were required and available evidence was sparse. They have been used to predict the evolution of the disease and to inform policy-making. In this paper, we address two kinds of epidemiological models widely used in the pandemic, namely, compartmental models and agent-based models. After describing their essentials—some real examples are invoked—we discuss their main strengths and weaknesses. Then, on the basis of this analysis, we make (...) a comparison between their respective merits concerning three different goals: prediction, explanation, and intervention. We argue that there are general considerations which could favour any of those sorts of models for obtaining the aforementioned goals. We conclude, however, that preference for particular models must be grounded case-by-case since additional contextual factors, as the peculiarities of the target population and the aims and expectations of policy-makers, cannot be overlooked. (shrink)

The comprehension of norms in complex social systems is one of the most active fields of research in agent-based modelling. This is faced with the challenge to comprehend the recursive interaction between inter- and intra-agent processes. In this article, a comparative analysis of selected cases of normative agent architectures will be given based on a review of theories of norms in the social sciences. This allows to identify the prerequisites for a representation of the cognitive processes of norm recognition. As (...) yet, there is no unequivocal concept for the design of normative agents. Different approaches are compared along the line of different theoretical accounts. (shrink)

Making good decisions depends on having accurate information – quickly, and in a form in which it can be readily communicated and acted upon. Two features of medical practice can help: deliberation in groups and the use of scores and grades in evaluation. We study the contributions of these features using a multi-agent computer simulation of groups of physicians. One might expect individual differences in members’ grading standards to reduce the capacity of the group to discover the facts on which (...) well-informed decisions depend. Observations of the simulated groups suggest on the contrary that this kind of diversity can in fact be conducive to epistemic performance. Sometimes, it is adopting common standards that may be expected to result in poor decisions. (shrink)

Network theory is applied across the sciences to study phenomena as diverse as the spread of SARS, the topology of the cell, the structure of the Internet and job search behaviour. Underlying the study of networks is graph theory. Whether the graph represents a network of neurons, cells, friends or firms, it displays features that exclusively depend on the mathematical properties of the graph itself. However, the way in which graph theory is implemented to the modelling of networks differs significantly (...) across scientific fields. This article compares the economics variant of network theory with those of other fields. It shows how the methodology employed by economists to model networks is shaped by two explanatory desiderata: that the explanandum phenomenon is based on micro-economic foundations and that the explanation is general. (shrink)

Social scientists associate agent-based simulation (ABS) models with three ideas about explanation: they provide generative explanations, they are models of mechanisms, and they implement methodological individualism. In light of a philosophical account of explanation, we show that these ideas are not necessarily related and offer an account of the explanatory import of ABS models. We also argue that their bottom-up research strategy should be distinguished from methodological individualism.

This article aims at contributing to the discussion about the relationships between ICT, computer science and policy-making by focusing on agent-based social simulation. Enabled, from a technical point of view, by the developments of Distributed Artificial Intelligence in the 1990s and by the features of the object-oriented programming paradigm, agent-based social simulations are a tool for the analysis of social dynamics that can be used also to support the design and the evaluation of public policies. After a brief description of (...) social simulation paradigm and of its impact on social sciences, the paper presents a simple agent-based model devised to analyze, even if in a very abstract way, a phenomenon that can rouse the interest of legal scientists: the interplay between damaging behaviors, punishment and social mechanisms of learning and imitation. Our goal is to show how agent-based simulation can be used not only to illuminate basic mechanisms underlying social phenomena but also to reflect, in an innovative way, on how society can deal with them. (shrink)

Redish et al. rely too much on a rational and innate view of decision-making, when their emphasis on variation, their integrative spirit, and their neuroscientific insights point towards a broader view of why addiction is such a tenacious problem. The integration of subjective, sociocultural, and evolutionary factors with cognitive neuroscience advances our understanding of addiction and decision-making.

Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these essential properties imply real-world economies are locally-constructive sequential games. This paper discusses a modeling approach, (...) Agent-based Computational Economics, that permits researchers to study economic systems from this point of view. ACE modeling principles and objectives are first concisely presented and explained. The remainder of the paper then highlights challenging issues and edgier explorations that ACE researchers are currently pursuing. (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)

The model proposed by Redish et al. considers vulnerabilities within decision systems based on expectancy-value assumptions. Further understanding of processes leading to addiction can be gained by considering other inputs to decision-making, particularly affective associations with behaviors. This consideration suggests additional decision-making vulnerabilities that might explain addictive behaviors.

Agent-based models are increasingly important in social science research. They have two obvious apparent virtues: they can model complex macrosociological phenomena without strong assumptions about agents and without analytic solutions for models, and they seem to instantiate the methodological individualist program in a concrete way. We argue that the latter claim is false. After providing schematic accounts of ABM models and a first introduction to ways in which to characterize individualist explanations, we work through six conceptions of individualist explanations that (...) are decreasingly "less individualist" and argue that ABM-based explanations in the social sciences are not inevitably individualist in any of these senses. ABMs allow for explanatory relations among social entities and properties in the model environment and they are silent on what basic agents are, allowing social entities and properties to play basic explanatory roles. (shrink)

Complexity science has witnessed a number of advances since the publication of Jervis's System Effects. These advances better allow us to untangle the messy elements in a system and predict sets of likely outcomes. However, just because a system is complex doesn't mean that all the ideas relating to complexity—such as agent-based modeling, path dependency, tipping points, between-class versus within-class effects, and networks—are necessarily relevant. One of our tasks is to determine whether they are—and, if so, their implications. As examples, (...) we use China's role in the formation of the United States housing bubble; the federal government's bailout of AIG and Bear Stearns but not Lehman Brothers; and China's failure to experience a regime change such as the Middle East's Arab Spring. (shrink)

The emergentist position that R. Keith Sawyer has formulated, nonreductive individualism, contains three propositions. First, that social characteristics must always be realized in individuals; second, that it is nevertheless possible to understand social properties as irreducible; and third, that therefore it is possible to demonstrate how social properties are able to exercise independent causal influences on individuals and their properties. It is demonstrated that Sawyer is not able to meet an objection that Kim has formulated against the analogous position in (...) the philosophy of mind. In his defense of the claim of irreducibility Sawyer refers to Fodor’s argument about multiple realizability, but this line of argument cannot preserve the claim for downward causation because Fodor’s claim for irreducibility rests on assumptions that are not compatible with a systematic formulation of downward causation. The article proposes a reading of Fodor’s argument that is consistent with individualism but not with nonreductive individualism. (shrink)

The resurgence of interest in collective behavior is in large part due to tools recently made available for conducting laboratory experiments on groups, statistical methods for analyzing large data sets reflecting social interactions, the rapid growth of a diverse variety of online self‐organized collectives, and computational modeling methods for understanding both universal and scenario‐specific social patterns. We consider case studies of collective behavior along four attributes: the primary motivation of individuals within the group, kinds of interactions among individuals, typical dynamics (...) that result from these interactions, and characteristic outcomes at the group level. With this framework, we compare the collective patterns of noninteracting decision makers, bee swarms, groups forming paths in physical and abstract spaces, sports teams, cooperation and competition for resource usage, and the spread and extension of innovations in an online community. Some critical issues surrounding collective behavior are then reviewed, including the questions of “Does group behavior always reduce to individual behavior?”“Is ‘group cognition’ possible?” and “What is the value of formal modeling for understanding group behavior?”. (shrink)

Tarski’s conceptual analysis of the notion of logical consequence is one of the pinnacles of the process of defining the metamathematical foundations of mathematics in the tradition of his predecessors Euclid, Frege, Russell and Hilbert, and his contemporaries Carnap, Gödel, Gentzen and Turing. However, he also notes that in defining the concept of consequence “efforts were made to adhere to the common usage of the language of every day life.” This paper addresses the issue of what relationship Tarski’s analysis, and (...) Béziau’s further generalization of it in universal logic, have to reasoning in the everyday lives of ordinary people from the cognitive processes of children through to those of specialists in the empirical and deductive sciences. It surveys a selection of relevant research in a range of disciplines providing theoretical and empirical studies of human reasoning, discusses the value of adopting a universal logic perspective, answers the questions posed in the call for this special issue, and suggests some specific research challenges. (shrink)

This article considers the implications of complex systems models for the study of economics and the evaluation of public policies. I argue that complexity can enhance current approaches to formal economic analysis, but does so in ways that complement current approaches. I further argue that while complexity can influence how public policy analysis is conducted, it does not delimit the use of consequentialist approaches to policy comparison to the degree initially suggested by Hayek and most recently defended by Gaus.

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)

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)

The necessity to model the mental ingredients of norm compliance is a controversial issue within the study of norms. So far, the simulation-based study of norm emergence has shown a prevailing tendency to model norm conformity as a thoughtless behavior, emerging from social learning and imitation rather than from specific, norm-related mental representations. In this paper, the opposite stance—namely, a view of norms as hybrid, two-faceted phenomena, including a behavioral/social and an internal/mental side—is taken. Such a view is aimed at (...) accounting for the difference between norms, on one hand, and either behavioral regularities (conventions) on the other. This paper, in particular, is addressed to find out the internal ingredients required for the former distinction, i.e., to model norms as distinct from mere conventions, and defined as behaviors spreading to the extent that and because the corresponding commands and beliefs do spread as well. After a brief presentation of a normative agent architecture, the results of agent-based simulations testing the impact of norm recognition and the role of normative beliefs in the emergence and innovation of social norms are presented and discussed. More specifically, the present work will endeavour to show that a sudden external constraint (e.g. a barrier preventing agents from moving among social settings) facilitates norm innovation: under such a condition, agents provided with a module for telling what a norm is can generate new (social) norms by forming new normative beliefs, irrespective of the most frequent actions. (shrink)

This paper's purpose is to set forth the conditions of explanation in the domain of formal modelling of social action. Explanation is defined as an adequate account of the underlying factors bringing about a phenomenon. The modelling of a social phenomenon can claim explanatory value in this sense if the following two conditions are fulfilled. (1) The generative mechanisms involved translate the effects of real factors abstracted from their phenomenal context, not those of purely ideal ones. (2) The explanatory hypotheses, (...) which account for the effects of explanatory factors, and the purely descriptive hypotheses, which introduce conceptual simplifications and summarise complex secondary mechanisms, are relatively independent from each other with regard to the phenomenon represented. This condition subjects the model to testing by alternatives through the development of purely descriptive hypotheses in the sense of explanatory or analytical realism. (shrink)

The explanatory power of structures in analytical sociologists’ agent-based models brings into question methodological individualism. We defend that from an explanatory point of view, the syntactic properties of models require semantic conditions of interpretation drawn from a conceptual research framework; in such a framework, social/relational structures have only partial, explanatory power ; and taking the explanation further through generative mechanism modeling necessitates calling upon methodological individualism’s generic framework of interpretation that relies on social actors’ rational capacity. According to this interpretive (...) framework, forces in action in society are governed by the subjective meaning of/the reasons for individual actions. (shrink)

Philosophers and social scientists have recently turned to game theory and agent-based models to better understand social contract formation. The stag hunt game is an idealization of social contract formation. Using the stag hunt game, we attempt to determine what, if any, barrier diversity is to the formation of an efficient social contract. We uncover a deep connection between tolerance, diversity, and the social contract. We investigate a simple model in which individuals possess salient traits and behave cooperatively when the (...) difference between their trait and the trait of their counterpart is less than their ‘tolerance level’. If traits are fixed and correspond to permanent or semipermanent features of the individual, such as religion or race, social contract formation is a remote possibility. If traits are malleable, social contract formation is possible but comes at the steep cost of diversity and tolerance, that is, individuals are unwilling to cooperate with those much different from themselves. Yet homogeneity and intolerance are not a long-term feature of the population. Over time mutations allow for increasingly tolerant agents to prosper, thereby ushering in trait diversity. In the end, all reap the benefits of cooperation. (shrink)

Polarization is a topic of intense interest among social scientists, but there is significant disagreement regarding the character of the phenomenon and little understanding of underlying mechanics. A first problem, we argue, is that polarization appears in the literature as not one concept but many. In the first part of the article, we distinguish nine phenomena that may be considered polarization, with suggestions of appropriate measures for each. In the second part of the article, we apply this analysis to evaluate (...) the types of polarization generated by the three major families of computational models proposing specific mechanisms of opinion polarization. (shrink)

The development of new theory is often spurred by novel techniques that provide better answers to existing questions, or that allow asking new ones. In the field of strategy and organization science, models of complex adaptive systems have renewed theoretical work on a fundamental question: how organizations can adapt effectively to their environments. This article has three objectives: to highlight some areas where models of organizations as complex adaptive systems have made substantial contributions: the search for solutions to sets of (...) interdependent choices, the challenge of balancing processes of exploration and exploitation, and the organization of imperfect decision makers; to point to several challenges and tradeoffs which can limit the explanatory power and eventual impact of the modeling enterprise; and to sketch out possible future directions of research that would do further justice to the notion of organizations as complex adaptive systems. (shrink)

As figurational sociologists and sociolinguists, we need to know that we currently find support from other fields in our efforts to construct a sociocultural science focused on interdependencies and processes, creating a multidimensional picture of human beings, one in which the brain and its mental and emotional processes are properly recognized. The paradigmatic revolutions in 20th-century physics, the contributions made by biology to our understanding of living beings, the conceptual constructions built around the theories of systems, self-organization and complexity, all (...) these implore that we reflect on social sciences paradigms in the light of the great changes in these other disciplines. The application of metaphors or theoretical images of complexity and figurational sociology in understanding language and socio-communication phenomena is of great use, since language is not an ‘object’, but a ‘complex’; it exists simultaneously in and among different domains. ‘Languaging’ and interaction are co-phenomena. The former exists within the latter, and the latter within the former. By visualizing, for instance, the different levels of linguistic structure not as separate entities but rather as united and integrated within the same theoretical frame, by seeing their functional interdependencies, by situating them in a greater multidimensionality that includes what for a long time was considered ‘external’ – the individual and his or her mind-brain, the sociocultural system, the physical world, etc. – and expanding in this way our classical view, we should be able to make important, if not essential, theoretical and practical advances. (shrink)

Even though the philosophy of simulation is intended as a comprehensive reflection about the practice of computer simulation in contemporary science, its output has been disproportionately shaped by research on equation-based simulation in the physical and climate sciences. Hence, the particularities of alternative practices of computer simulation in other scientific domains are not sufficiently accounted for in the current philosophy of simulation literature. This article centres on agent-based social simulation, a relatively established type of simulation in the social sciences, to (...) exemplify this claim. The analysis advanced has a twofold goal. First, it shows that the philosophy of agent-based social simulation, mostly developed by practitioners themselves, is, on one hand, heavily influenced by the methodological features of agent-based modelling and by the loose and fragmented character of social theory and, on the other hand, distinctively shaped by contrasting views of what it implies to do social research with virtual or artificial societies. Second, it suggests ways in which cross-fertilisation could enrich the philosophical understanding of computer simulation both in agent-based social simulation and in the philosophy of simulation. (shrink)