This study provides a basic introduction to agent-based modeling (ABM) as a powerful blend of classical and constructive mathematics, with a primary focus on its applicability for social science research. The typical goals of ABM social science researchers are discussed along with the culture-dish nature of their computer experiments. The applicability of ABM for science more generally is also considered, with special attention to physics. Finally, two distinct types of ABM applications are summarized in order to illustrate (...) concretely the duality of ABM: Real-world systems can not only be simulated with verisimilitude using ABM; they can also be efficiently and robustly designed and constructed on the basis of ABM principles. (shrink)

Agent-​​based modeling is showing great promise in the social sciences. However, two misconceptions about the relation between social macroproperties and microproperties afflict agent-based models. These lead current models to systematically ignore factors relevant to the properties they intend to model, and to overlook a wide range of model designs. Correcting for these brings painful trade-​​offs, but has the potential to transform the utility of such models.

Agent-based models have played a prominent role in recent debates about the merits of democracy. In particular, the formal model of Lu Hong and Scott Page and the associated “diversity trumps ability” result has typically been seen to support the epistemic virtues of democracy over epistocracy (i.e., governance by experts). In this paper we first identify the modeling choices embodied in the original formal model and then critique the application of the Hong-Page results to philosophical debates on (...) the relative merits of democracy. In particular we argue that the “best-performing agents” in Hong-Page model should not be interpreted as experts. We next explore a closely related model in which best-performing agents are more plausibly seen as experts and show that the diversity trumps ability result fails to hold. However, with changes in other parameters (such as the deliberation dynamic) the diversity trumps ability result is restored. The sensitivity of this result to parameter choices illustrates the complexity of the link between formal modeling and more general philosophical claims; we use this debate as a platform for a more general discussion of when and how agent-based models can contribute to philosophical discussions. (shrink)

Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition, strategic interaction, collective learning, and the possibility of multiple equilibria. Recent advances in analytical and computational tools are permitting new approaches to the quantitative study of these aspects. One such approach is Agent-based Computational Economics (ACE), the computational study of economic processes modeled (...) as dynamic systems of interacting agents. This chapter explores the potential advantages and disadvantages of ACE for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, institutional arrangements, and behavioral dispositions. (shrink)

What endogenous factors contribute to minority (Red Queen) or majority (Red King) domination under conditions of coercive bargaining? We build on previous work demonstrating minority disadvantage in non-coercive bargaining games to show that under neutral initial conditions, majorities are advantaged in high conflict situations, and minorities are advantaged in low conflict games. These effects are a function of the relationship between (1) relative proportions of the majority and minority groups and (2) costs of conflict. Although both Red King and Red (...) Queen effects can occur, we further show that agents’ increased initial propensity toward conflict advantages majorities. (shrink)

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)

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)

Public health care interventions—regarding vaccination, obesity, and HIV, for example—standardly take the form of information dissemination across a community. But information networks can vary importantly between different ethnic communities, as can levels of trust in information from different sources. We use data from the Greater Pittsburgh Random Household Health Survey to construct models of information networks for White and Black communities--models which reflect the degree of information contact between individuals, with degrees of trust in information from various sources correlated with (...) positions in that social network. With simple assumptions regarding belief change and social reinforcement, we use those modeled networks to build dynamic agent-based models of how information can be expected to flow and how beliefs can be expected to change across each community. With contrasting information from governmental and religious sources, the results show importantly different dynamic patterns of belief polarization within the two communities. (shrink)

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the field. (...) Moreover, we argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond. (shrink)

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 (...) class='Hi'>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)

Modeling social interactions based on individual behavior has always been an area of interest, but prior literature generally presumes rational behavior. Thus, such models may miss out on capturing the effects of biases humans are susceptible to. This work presents a method to model egocentric bias, the real-life tendency to emphasize one's own opinion heavily when presented with multiple opinions. We use a symmetric distribution, centered at an agent's own opinion, as opposed to the Bounded Confidence (BC) (...) model used in prior work. We consider a game of iterated interactions where an agent cooperates based on its opinion about an opponent. Our model also includes the concept of domain-based self-doubt, which varies as the interaction succeeds or not. An increase in doubt makes an agent reduce its egocentricity in subsequent interactions, thus enabling the agent to learn reactively. The agent system is modeled with factions not having a single leader, to overcome some of the issues associated with leader-follower factions. We find that agents belonging to factions perform better than individual agents. We observe that an intermediate level of egocentricity helps the agent perform at its best, which concurs with conventional wisdom that neither overconfidence nor low self-esteem brings benefits. (shrink)

Ecological-enactive approaches to cognition aim to explain cognition in terms of the dynamic coupling between agent and environment. Accordingly, cognition of one’s immediate environment (which is sometimes labeled “basic” cognition) depends on enaction and the picking up of affordances. However, ecological-enactive views supposedly fail to account for what is sometimes called “higher” cognition, i.e., cognition about potentially absent targets, which therefore can only be explained by postulating representational content. This challenge levelled against ecological-enactive approaches highlights a putative explanatory gap (...) between basic and higher cognition. In this paper, we examine scientific cognition—a paradigmatic case of higher cognition—and argue that it shares fundamental features with basic cognition, for enaction and affordance selection are central to the scientific enterprise. Our argument focuses on modeling, and on how models promote scientific understanding. We base our argument on a non-representational account of scientific understanding and on the material engagement theory, for models are hereby conceived as material objects designed for scientific engagements. Having done so, we conclude that the explanatory gap is significantly less threatening to the ecological-enactive approach than it might appear. (shrink)

The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the (...) core of the FMSA is similar in both contexts: notions of “levels of system specifi cation”, “behavior of models”, “simulator”and “endomorphic agents” can be partially translated in the terms linked to the “denotational hierarchy” (DH) recently introduced in a multi-level centered epistemology of M&S. Second, we suggest considering the question of “credibility” of agent M&S in social sciences when we do not try to emulate but only to simulate target systems. Whereas a stringent and standardized treatment of the heterogeneous internal relations (in the DH) between systems of formalisms is the key problem and the essential challenge in the scope of Agent M&S driven engineering, it is urgent too to address the problem of the external relations (and of the external validity, hence of the epistemic power and credibility) of such levels of formalisms in the specific domains of agent M&S in social sciences, especially when we intend to introduce the concepts of activity tracking. (shrink)

Previous simulation models have found positive effects of cognitive diversity on group performance, but have not explored effects of diversity in demographics (e.g., gender, ethnicity). In this paper, we present an agent-based model that captures two empirically supported hypotheses about how demographic diversity can improve group performance. The results of our simulations suggest that, even when social identities are not associated with distinctive task-related cognitive resources, demographic diversity can, in certain circumstances, benefit collective performance by counteracting two types (...) of conformity that can arise in homogeneous groups: those relating to group-based trust and those connected to normative expectations towards in-groups. (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 tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, section (...) 2 gives conceptual tools to explain the rationale of the diverse epistemological positions presented in section 1. Finally, we claim that a careful attention to the real multiplicity of denotational powers of symbols at stake and then to the implicit routes of references operated by models and computer simulations is necessary to determine, in each case, the proper epistemic status and credibility of a given model and/or simulation. (shrink)

An on-going question for virtue ethics is whether it stands as a truly distinctive approach to ethics. In particular, there has been much discussion of whether virtue ethics can provide a viable understanding of right action, one that is a genuine rival to familiar consequentialist and deontological accounts. In this chapter I examine two prominent approaches to virtue ethics, (i) qualified agent and (ii) agent-based virtue ethics, and consider whether either can provide an adequate account of right (...) action. I begin with a presentation of their accounts of right action, including consideration of what is meant by the term “right action”. With this groundwork in place, I turn to a series of important objections that have been raised against these accounts, and consider some of the more prominent and promising responses that these objections have inspired. (shrink)

Agent-based models (ABMs) are one type of simulation model used in the context of the COVID-19 pandemic. In contrast to equation-based models, ABMs are algorithms that use individual agents and attribute changing characteristics to each one, multiple times during multiple iterations over time. This paper focuses on three philosophical aspects of ABMs as models of causal mechanisms, as generators of emergent phenomena, and as providers of explanation. Based on my discussion, I conclude that while ABMs cannot (...) help much with causal inference, they can be viewed as etio-prognostic explanations of illness occurrence and outcome. (shrink)

Starting from a philosophical perspective, which states that the living structures are actually a combination between matter and information, this article presents the results on an analysis of the bipolar information-matter structure of the human organism, distinguishing three fundamental circuits for its survival, which demonstrates and supports this statement, as a base for further development of the informational model of consciousness to a general informational model of the human organism. For this, it was examined the Informational System of the Human (...) Body and its components from the perspective of the physics/information/neurosciences concepts, showing specific functions of each of them, highlighting the correspondence of these centers with brain support areas and with their projections in consciousness, which are: Center of Acquisition and Storing of Information (CASI) reflected in consciousness as memory, Center of Decision and Command (CDC) (decision), Info-Emotional Center (IES) (emotions), Maintenance Informational System (MIS) (personal status), Genetic Transmission System (GTS) (associativity/genetic transmission) and Info Genetic Generator (IGG) related by the body development and inherited behaviors. The Info Connection (IC), detected in consciousness as trust and confidence can explain the Near-Death Experiences (NDEs) and associated phenomena. This connection is antientropic and informational, because from the multitude of uncertain possibilities is selected a certain one, helping/supporting the survival and life. The human body appears therefore as a bipolar structure, connected to two poles: information and matter. It is argued that the survival, which is the main objective of the organism, is complied in three main ways, by means of: (i) the reactive operation for adaptation by attitude; (ii) the info-genetic integration of information by epigenetic processes and genetic transmission of information for species survival, both circuits (i) and (ii) being associated to the information pole; (iii) maintenance of the material body (defined as informed matter) and its functions, associated to the matter pole of the organism. It results therefore that the informational system of the human body is supported by seven informational circuits formed by the neuro-connections between the specific zones of the brain corresponding to the informational subsystems, the cognitive centers, the sensors, transducers and execution (motor/mobile) elements. The fundamental informational circuits assuring the survival are the reactive circuit, expressible by attitude, the epigenetic/genetic circuit, absorbing and codifying information to be transmitted to the next generations, and the metabolic circuit, connected to matter (matter pole). The presented analysis allows to extend the informational modeling of consciousness to an Informational Model of Consciousness and Organism, fully describing the composition/functions of the organism in terms of information/matter and neurosciences concept. (shrink)

Agent-based virtue ethical theories must deal with the problem of right action: if an action is right just in case it expresses a virtuous motive, then how can an agent perform the right action but for the wrong reason, or from a vicious motive? Some recent agent-based accounts purport to answer this challenge and two other related problems. Here I assess these accounts and show them to be inadequate answers to the problem of right action. (...) Overall, it is shown that the most recent and promising attempts at squaring agent-based virtue ethics with commonsense morality are flawed, and so, the case for agent-basing in general that much dimmer. (shrink)

Modelling ethics is critical to understanding and analysing social phenomena. However, prior literature either incorporates ethics into agent strategies or uses it for evaluation of agent behaviour. This work proposes a framework that models both, ethical decision making as well as evaluation using virtue ethics and utilitarianism. In an iteration, agents can use either the classical Continuous Prisoner's Dilemma or a new type of interaction called moral interaction, where agents donate or steal from other agents. We introduce moral (...) interactions to model ethical decision making. We also propose a novel agent type, called virtue agent, parametrised by the agent's level of ethics. Virtue agents' decisions are based on moral evaluations of past interactions. Our simulations show that unethical agents make short term gains but are less prosperous in the long run. We find that in societies with positivity bias, unethical agents have high incentive to become ethical. The opposite is true of societies with negativity bias. We also evaluate the ethicality of existing strategies and compare them to those of virtue agents. (shrink)

We present a theory of cooperative-competitive intelligence (CCI), its measures, research program, and applications that stem from it. Within the framework of this theory, satisficing sub-optimal behavior is any behavior that does not promote a decrease in the prospective control of the functional action diversity/unpredictability (D/U) potential of the agent or team. This potential is defined as the entropy measure in multiple, context-dependent dimensions. We define the satisficing interval of behaviors as CCI. In order to manifest itself at individual (...) or team level, this capacity harnesses properties such as degeneracy, pleiotropy (pluri-potentiality), synergies, and metastability. Intelligence is embodied because intelligent behavior is deeply dependent on body functionalities, defined as entropy measures. We base our theory on three principles: (a) relativity of functional entropy/ information in agent (team)-environment systems, (b) tendency toward the satisficing level of D/U potential, and (c) tendency toward the non-decreasing D/U potential. The conjunction of these three principles provides existence of sub-optimal behaviors associated with CCI. First, we deal with the problem of how to reduce multidimensional behavior to a concept that accounts for the vast set of scenarios in which CCI is manifested. Secondly, we define and discuss the three interacting principles that underpin CCI behavior as well as providing an outline for a future CCI research program supported by agent￾based modeling and empirical research. Finally, we provide some preliminary practical issues that stem from the theory. (shrink)

Kuhn wanted to install a new research agenda in philosophy of science. I argue that the tools are now available to better articulate his paradigm and let it guide philosophical research instead of itself remaining the object of philosophical debate.

This article argues for a task-based approach to identifying and individuating cognitive systems. The agent-based extended cognition approach faces a problem of cognitive bloat and has difficulty accommodating both sub-individual cognitive systems ("scaling down") and some supra-individual cognitive systems ("scaling up"). The standard distributed cognition approach can accommodate a wider variety of supra-individual systems but likewise has difficulties with sub-individual systems and faces the problem of cognitive bloat. We develop a task-based variant of distributed cognition designed (...) to scale up and down smoothly while providing a principled means of avoiding cognitive bloat. The advantages of the task-based approach are illustrated by means of two parallel case studies: re-representation in the human visual system and in a biomedical engineering laboratory. (shrink)

This article reports an exploratory survey of the structure of interdisciplinary research in Agent-Based Social Simulation. One hundred and ninety six researchers participated in the survey completing an on-line questionnaire. The questionnaire had three distinct sections, a classification of research domains, a classification of models, and an inquiry into software requirements for designing simulation platforms. The survey results allowed us to disambiguate the variety of scientific goals and modus operandi of researchers with a reasonable level of detail, and (...) to identify a classification of agent-based models used in simulation. In particular, in the interdisciplinary context of social-scientific modelling, agent-based computational modelling and computer engineering, we analyse the extent to which these paradigmatic models seem to be mutually instrumental in the field. We expect that our proposal may improve the viability of submitting, explaining and comparing agent-based simulations in articles, which is an important methodological requirement to consolidate the field. We also expect that it will motivate other proposals that could further validate, extend or change ours, in order to refine the classification with more types of models. (shrink)

The classical theory of computation does not represent an adequate model of reality for simulation in the social sciences. The aim of this paper is to construct a methodological perspective that is able to conciliate the formal and empirical logic of program verification in computer science, with the interpretative and multiparadigmatic logic of the social sciences. We attempt to evaluate whether social simulation implies an additional perspective about the way one can understand the concepts of program and computation. We demonstrate (...) that the logic of social simulation implies at least two distinct types of program verifications that reflect an epistemological distinction in the kind of knowledge one can have about programs. Computer programs seem to possess a causal capability (Fetzer, 1999) and an intentional capability that scientific theories seem not to possess. This distinction is associated with two types of program verification, which we call empirical and intentional verification. We demonstrate, by this means, that computational phenomena are also intentional phenomena, and that such is particularly manifest in agent-based social simulation. Ascertaining the credibility of results in social simulation requires a focus on the identification of a new category of knowledge we can have about computer programs. This knowledge should be considered an outcome of an experimental exercise, albeit not empirical, acquired within a context of limited consensus. The perspective of intentional computation seems to be the only one possible to reflect the multiparadigmatic character of social science in terms of agent-based computational social science. We contribute, additionally, to the clarification of several questions that are found in the methodological perspectives of the discipline, such as the computational nature, the logic of program scalability, and the multiparadigmatic character of agent-based simulation in the social sciences. (shrink)

“Epistemic Dexterity: A Ramseyian Account of Epistemic Virtue” by Abrol Fairweather & Carlos Montemayor: A modification of F.P. Ramsey’s success semantics supports a naturalized theory of epistemic virtue that includes motivational components and can potentially explain both epistemic reliability and responsibility with a single normative-explanatory principle. An “epistemic Ramsey success” will also provide a better account of the “because of” condition central to virtue-reliabilist accounts of knowledge from Greco, Sosa and Pritchard. Ramsey said that the truth condition of a belief (...) is the condition that guarantees the success of desires based on that belief. Taken as a theory of epistemic achievements, the truth condition for the attribution of an epistemic achievement is the condition that guarantees the success of epistemic desires and is also a success based on abilities attributable to the agent. One of its major advantages is that it may be the best way to achieve a naturalistic version of the etiologcal requirement on knowledge in virtue epistemology while also supporting important responsibilist desiderata. The account defended is robustly agent-centered in the straightforward sense that individual desires are partly constitutive of epistemic successes like having a rational belief, justified belief, and even of knowledge once we see the both the reliabilist and repsonsibilist desiderata are met. Another important aspect of the paper is that it provides a plausible psychology for virtue epistemology that is grounded in important empirical findings on agency, and thus constitutes a form of naturalized virtue epistemology. (shrink)

To reach sustainability transitions, we must learn to leverage social systems into tipping points, where societies exhibit positive-feedback loops in the adoption of sustainable behavioral and cultural traits. However, much less is known about the most efficient ways to reach such transitions or how self-reinforcing systemic transformations might be instigated through policy. We employ an agent-based model to study the emergence of social tipping points through various feedback loops that have been previously identified to constitute an ecological approach (...) to human behavior. Our model suggests that even a linear introduction of pro-environmental affordances (action opportunities) to a social system can have non-linear positive effects on the emergence of collective pro-environmental behavior patterns. We validate the model against data on the evolution of cycling and driving behaviors in Copenhagen. Our model gives further evidence and justification for policies that make pro-environmental behavior psychologically salient, easy, and the path of least resistance. (shrink)

Philosophical investigation in synthetic biology has focused on the knowledge-seeking questions pursued, the kind of engineering techniques used, and on the ethical impact of the products produced. However, little work has been done to investigate the processes by which these epistemological, metaphysical, and ethical forms of inquiry arise in the course of synthetic biology research. An attempt at this work relying on a particular area of synthetic biology will be the aim of this chapter. I focus on the reengineering of (...) metabolic pathways through the manipulation and construction of small DNA-based devices and systems synthetic biology. Rather than focusing on the engineered products or ethical principles that result, I will investigate the processes by which these arise. As such, the attention will be directed to the activities of practitioners, their manipulation of tools, and the use they make of techniques to construct new metabolic devices. Using a science-in-practice approach, I investigate problems at the intersection of science, philosophy of science, and sociology of science. I consider how practitioners within this area of synthetic biology reconfigure biological understanding and ethical categories through active modelling and manipulation of known functional parts, biological pathways for use in the design of microbial machines to solve problems in medicine, technology, and the environment. We might describe this kind of problem-solving as relying on what Helen Longino referred to as “social cognition” or the type of scientific work done within what Hasok Chang calls “systems of practice”. My aim in this chapter will be to investigate the relationship that holds between systems of practice within metabolic engineering research and social cognition. I will attempt to show how knowledge and normative valuation are generated from this particular network of practitioners. In doing so, I suggest that the social nature of scientific inquiry is ineliminable to both knowledge acquisition and ethical evaluations. (shrink)

Enterprise Risk Management involves the process of identification, evaluation, treatment, and communication regarding risks throughout the enterprise. To support the tasks associated with this process, several frameworks and modeling languages have been proposed, such as the Risk and Security Overlay (RSO) of ArchiMate. An ontological investigation of this artifact would reveal its adequacy, capabilities, and limitations w.r.t. the domain of risk and security. Based on that, a language redesign can be proposed as a refinement. Such analysis and redesign (...) have been executed for the risk elements of the RSO grounded in the Common Ontology of Value and Risk. The next step along this line of research is to address the following research problems: What would be the outcome of an ontological analysis of security-related elements of the RSO? That is, can we identify other semantic deficiencies in the RSO through an ontological analysis? Once such an analysis is provided, can we redesign the security elements of the RSO accordingly, in order to produce an improved artifact? Here, with the aid of the Reference Ontology for Security Engineering (ROSE) and the ontological theory of prevention behind it, we address the remaining gap by proceeding with an ontological analysis of the security-related constructs of the RSO. The outcome of this assessment is an ontology-based redesign of the ArchiMate language regarding security modeling. In a nutshell, we report the following contributions: (1) an ontological analysis of the RSO that identifies six limitations concerning security modeling; (2) because of the key role of the notion of prevention in security modeling, the introduction of the ontological theory of prevention in ArchiMate; (3) a well-founded redesign of security elements of ArchiMate; and (4) ontology-based security modeling patterns that are logical consequences of our proposal of redesign due to its underlying ontology of security. As a form of evaluation, we show that our proposal can describe risk treatment options, according to ISO 31000. Finally, besides presenting multiple examples, we proceed with a real-world illustrative application taken from the cybersecurity domain. (shrink)

This paper introduces a generic agent-based model simulating the exchange and the diffusion of pro and con arguments. It is applied to the case of the diffusion of vegetarian diets in the context of a potential emergence of a second nutrition transition. To this day, agent-based simulation has been extensively used to study opinion dynamics. However, the vast majority of existing models have been limited to extremely abstract and simplified representations of the diffusion process. These simplifications (...) impairs the realism of the simulations and disables the understanding of the reasons for the shift of an actor's opinion. The generic model presented here explicitly represents exchanges of arguments between actors in the context of an opinion dynamic model. In particular, the inner attitude towards an opinion of each agent is formalized as an argumentation graph and each agent can share arguments with other agents. Simulation experiments show that introducing attacks between arguments and a limitation of the number of arguments mobilized by agents has a strong impact on the evolution of the agents' opinion. We also highlight that when a new argument is introduced into the system, the quantity and the profile of the agents receiving the new argument will impact the evolution of the overall opinion. Finally, the application of this model to vegetarian diet adoption seems consistent with historical food behaviour dynamics observed during crises. (shrink)

Although there have been efforts to integrate Semantic Web technologies and artificial agents related AI research approaches, they remain relatively isolated from each other. Herein, we introduce a new ontology framework designed to support the knowledge representation of artificial agents’ actions within the context of the actions of other autonomous agents and inspired by standard cognitive architectures. The framework consists of four parts: 1) an event ontology for information pertaining to actions and events; 2) an epistemic ontology containing facts about (...) knowledge, beliefs, perceptions and communication; 3) an ontology concerning future intentions, desires, and aversions; and, finally, 4) a deontic ontology for modeling obligations and prohibitions which limit agents’ actions. The architecture of the ontology framework is inspired by deontic cognitive event calculus as well as epistemic and deontic logic. We also describe a case study in which the proposed DCEO ontology supports autonomous vehicle navigation. (shrink)

Across various fields it is argued that the self in part consists of an autobiographical self-narrative and that the self-narrative has an impact on agential behavior. Similarly, within action theory, it is claimed that the intentional structure of coherent long-term action is divided into a hierarchy of distal, proximal, and motor intentions. However, the concrete mechanisms for how narratives and distal intentions are generated and impact action is rarely fleshed out concretely. We here demonstrate how narratives and distal intentions can (...) be generated within cognitive agents and how they can impact agential behavior over long time scales. We integrate narratives and distal intentions into the LIDA model,and demonstrate how they can guide agential action in a manner that is consistent with the Global Workspace Theory of consciousness. This paper serves both as an addition to the LIDA cognitive architecture and an elucidation of how narratives and distal intention emerge and play their role in cognition and action. (shrink)

The geosciences include a wide spectrum of disciplines ranging from paleontology to climate science, and involve studies of a vast range of spatial and temporal scales, from the deep-time history of microbial life to the future of a system no less immense and complex than the entire Earth. Modeling is thus a central and indispensable tool across the geosciences. Here, we review both the history and current state of model-based inquiry in the geosciences. Research in these fields makes (...) use of a wide variety of models, such as conceptual, physical, and numerical models, and more specifically cellular automata, artificial neural networks, agent-based models, coupled models, and hierarchical models. We note the increasing demands to incorporate biological and social systems into geoscience modeling, challenging the traditional boundaries of these fields. Understanding and articulating the many different sources of scientific uncertainty – and finding tools and methods to address them – has been at the forefront of most research in geoscience modeling. We discuss not only structuralmodel uncertainties, parameter uncertainties, and solution uncertainties, but also the diverse sources of uncertainty arising from the complex nature of geoscience systems themselves. Without an examination of the geosciences, our philosophies of science and our understanding of the nature of model-based science are incomplete. (shrink)

This article takes off from Johan van Benthem’s ruminations on the interface between logic and cognitive science in his position paper “Logic and reasoning: Do the facts matter?”. When trying to answer Van Benthem’s question whether logic can be fruitfully combined with psychological experiments, this article focuses on a specific domain of reasoning, namely higher-order social cognition, including attributions such as “Bob knows that Alice knows that he wrote a novel under pseudonym”. For intelligent interaction, it is important that the (...) participants recursively model the mental states of other agents. Otherwise, an international negotiation may fail, even when it has potential for a win-win solution, and in a time-critical rescue mission, a software agent may depend on a teammate’s action that never materializes. First a survey is presented of past and current research on higher-order social cognition, from the various viewpoints of logic, artificial intelligence, and psychology. Do people actually reason about each other’s knowledge in the way proscribed by epistemic logic? And if not, how can logic and cognitive science productively work together to construct more realistic models of human reasoning about other minds? The paper ends with a delineation of possible avenues for future research, aiming to provide a better understanding of higher-order social reasoning. The methodology is based on a combination of experimental research, logic, computational cognitive models, and agent-based evolutionary models. Keywords Epistemic logic - Cognitive science - Intelligent interaction - Cognitive modeling. (shrink)

Temporal epistemic logics are known, from results of Halpern and Vardi, to have a wide range of complexities of the satisfiability problem: from PSPACE, through non-elementary, to highly undecidable. These complexities depend on the choice of some key parameters specifying, inter alia, possible interactions between time and knowledge, such as synchrony and agents' abilities for learning and recall. In this work we develop practically implementable tableau-based decision procedures for deciding satisfiability in single-agent synchronous temporal-epistemic logics with interactions between (...) time and knowledge. We discuss some complications that occur, even in the single-agent case, when interactions between time and knowledge are assumed and show how the method of incremental tableaux can be adapted to work in EXPSPACE, respectively 2EXPTIME, for these logics, thereby also matching the upper bounds obtained for them by Halpern and Vardi. (shrink)

John Stuart Mill advocated for increased interactions between individuals of dissenting opinions for the reason that it would improve society. Whether Mill and similar arguments that advocate for opinion diversity are valid depends on background assumptions about the psychology and sociality of individuals. The field of opinion dynamics is a burgeoning testing ground for how different combinations of sociological and psychological facts contribute to phenomena that affect opinion diversity, such as polarization. This paper applies some recent results from the opinion (...) dynamics literature to assess the impacts of the Millian suggestion. The goal is to understand how the scope of the validity of Mill-style arguments depends on plausible assumptions that can be formalized using agent-based models, a common modeling approach in opinion dynamics. The most salient insight is that homophily (increased interactions between like-minded individuals) does not sufficiently explain decreased opinion diversity. Hence, decreasing homophily by increasing interactions between individuals of dissenting opinions is not the simple solution that a Millian-style argument may advocate. (shrink)

The paper aims to explore what it means for something to be a social cycle, for a theory to be a social cycle theory, and to offer a suggestion for a simple, yet, we believe, fundamentally grounded schema for categorizing them. We show that a broad range of cycle theories can be described within the concept of disruption and adjustments. Further, many important cycle theories are true endogenous social cycle theories in which the theory provides a reason why the cycle (...) should recur. We find that many social cycle theories fit with a two-population disruption and adjustment model similar to the well-known predator-prey model. This implies that a general modeling framework could be established for creating agent-based models of many social cycle theories. (shrink)

In an ever-changing world, when we search for answers on our present challenges, it can be tricky to extrapolate past realities when concerning science-based issues. Climate change, public health or artificial intelligence embody issues on how scientific evidence is often challenged, as false beliefs could drive the design of public policies and legislation. Therefore , how can we foresee if science can tip the scales of political legislation? In this article, we outline how models of historical cases can be (...) used to predict and understand how scientific evidence can influence the emergence (or fall-back) of science based-legislation. We also present frameworks on how to use past episodes of History of Science and Alternative History insights to build epistemic models, based on previous successful approaches on the spread of scientific misinformation. These models will help the accuracy of the design of eventual alternative realities, that can come insightful on present decision making methodologies. (shrink)

Artificial Social Agents (ASAs), which are AI software driven entities programmed with rules and preferences to act autonomously and socially with humans, are increasingly playing roles in society. As their sophistication grows, humans will share greater amounts of personal information, thoughts, and feelings with ASAs, which has significant ethical implications. We conducted a study to investigate what ethical principles are of relative importance when people engage with ASAs and whether there is a relationship between people’s values and the ethical principles (...) they prioritise. The study uses scenarios, embedded with the five AI4People ethical principles (Beneficence, Non-maleficence, Autonomy, Justice, and Explicability), involving ASAs taking on roles traditionally played by humans to understand whether these roles and behaviours (including dialogues) are seen as acceptable or unacceptable. Results from 268 participants reveal the greatest sensitivity to ASA behaviours that relate to Autonomy, Justice, Explicability, and the privacy of their personal data. Models were created using Schwartz’s Refined Values as a possible indicator of how stakeholders discern and prioritise the different AI4People ethical principles when interacting with ASAs. Our findings raise issues around the ethical acceptability of ASAs for nudging and changing behaviour due to participants’ desire for autonomy and their concerns over deceptive ASA behaviours such as pretending to have memories and emotions. (shrink)

In this paper, a horizontally moving suspended mass pendulum base is designed and controlled using robust control theory. H  optimal loop shaping with first and second order desired loop shaping function controllers are used to improve the performance of the system using Matlab/Simulink Toolbox. Comparison of the H  optimal loop shaping with first and second order desired loop shaping function controllers for the proposed system have been done to track the desired angular position of the pendulum using step (...) and sine wave input signals and a promising result has been obtained succesfully. (shrink)

This paper focuses on the research field of machine ethics and how it relates to a technological singularity—a hypothesized, futuristic event where artificial machines will have greater-than-human-level intelligence. One problem related to the singularity centers on the issue of whether human values and norms would survive such an event. To somehow ensure this, a number of artificial intelligence researchers have opted to focus on the development of artificial moral agents, which refers to machines capable of moral reasoning, judgment, and decision-making. (...) To date, different frameworks on how to arrive at these agents have been put forward. However, there seems to be no hard consensus as to which framework would likely yield a positive result. With the body of work that they have contributed in the study of moral agency, philosophers may contribute to the growing literature on artificial moral agency. While doing so, they could also think about how the said concept could affect other important philosophical concepts. (shrink)

This article takes off from Johan van Benthem’s ruminations on the interface between logic and cognitive science in his position paper “Logic and reasoning: Do the facts matter?”. When trying to answer Van Benthem’s question whether logic can be fruitfully combined with psychological experiments, this article focuses on a specific domain of reasoning, namely higher-order social cognition, including attributions such as “Bob knows that Alice knows that he wrote a novel under pseudonym”. For intelligent interaction, it is important that the (...) participants recursively model the mental states of other agents. Otherwise, an international negotiation may fail, even when it has potential for a win-win solution, and in a time-critical rescue mission, a software agent may depend on a teammate’s action that never materializes. First a survey is presented of past and current research on higher-order social cognition, from the various viewpoints of logic, artificial intelligence, and psychology. Do people actually reason about each other’s knowledge in the way proscribed by epistemic logic? And if not, how can logic and cognitive science productively work together to construct more realistic models of human reasoning about other minds? The paper ends with a delineation of possible avenues for future research, aiming to provide a better understanding of higher-order social reasoning. The methodology is based on a combination of experimental research, logic, computational cognitive models, and agent-based evolutionary models. (shrink)

How do conventions of communication emerge? How do sounds or gestures take on a semantic meaning, and how do pragmatic conventions emerge regarding the passing of adequate, reliable, and relevant information? My colleagues and I have attempted in earlier work to extend spatialized game theory to questions of semantics. Agent-based simulations indicate that simple signaling systems emerge fairly naturally on the basis of individual information maximization in environments of wandering food sources and predators. Simple signaling emerges by means (...) of any of various forms of updating on the behavior of immediate neighbors: imitation, localized genetic algorithms, and partial training in neural nets. Here the goal is to apply similar techniques to questions of pragmatics. The motivating idea is the same: the idea that important aspects of pragmatics, like important aspects of semantics, may fall out as a natural results of information maximization in informational networks. The attempt below is to simulate fundamental elements of the Gricean picture: in particular, to show within networks of very simple agents the emergence of behavior in accord with the Gricean maxims. What these simulations suggest is that important features of pragmatics, like important aspects of semantics, don't have to be added in a theory of informational networks. They come for free. (shrink)

We apply spatialized game theory and multi-agent computational modeling as philosophical tools: (1) for assessing the primary social psychological hypothesis regarding prejudice reduction, and (2) for pursuing a deeper understanding of the basic mechanisms of prejudice reduction.

The mental risk poses a high threat to the individuals, especially overseas demographic, including expatriates in comparison to the general Arab demographic. Since Arab countries are renowned for their multicultural environment with half of the population of students and faculties being international, this paper focuses on a comprehensive analysis of mental health problems such as depression, stress, anxiety, isolation, and other unfortunate conditions. The dataset is developed from a web-based survey. The detailed exploratory data analysis is conducted on the (...) dataset collected from Arab countries to study an individual’s mental health and indicative help-seeking pointers based on their responses to specific pre-defined questions in a multicultural society. The proposed model validates the claims mathematically and uses different machine learning classifiers to identify individuals who are either currently or previously diagnosed with depression or demonstrate unintentional “save our souls” (SOS) behaviors for an early prediction to prevent risks of danger in life going forward. The accuracy is measured by comparing with the classifiers using several visualization tools. This analysis provides the claims and authentic sources for further research in the multicultural public medical sector and decision-making rules by the government. (shrink)

In the last few decades the role played by models and modeling activities has become a central topic in the scientific enterprise. In particular, it has been highlighted both that the development of models constitutes a crucial step for understanding the world and that the developed models operate as mediators between theories and the world. Such perspective is exploited here to cope with the issue as to whether error-based and uncertainty-based modeling of measurement are incompatible, and (...) thus alternative with one another, as sometimes claimed nowadays. The crucial problem is whether assuming this standpoint implies definitely renouncing to maintain a role for truth and the related concepts, particularly accuracy, in measurement. It is argued here that the well known objections against true values in measurement, which would lead to refuse the concept of accuracy as non-operational, or to maintain it as only qualitative, derive from a not clear distinction between three distinct processes: the metrological characterization of measuring systems, their calibration, and finally measurement. Under the hypotheses that (1) the concept of true value is related to the model of a measurement process, (2) the concept of uncertainty is related to the connection between such model and the world, and (3) accuracy is a property of measuring systems (and not of measurement results) and uncertainty is a property of measurement results (and not of measuring systems), not only the compatibility but actually the conjoint need of error-based and uncertainty-based modeling emerges. (shrink)

The optimality approach to modeling natural selection has been criticized by many biologists and philosophers of biology. For instance, Lewontin (1979) argues that the optimality approach is a shortcut that will be replaced by models incorporating genetic information, if and when such models become available. In contrast, I think that optimality models have a permanent role in evolutionary study. I base my argument for this claim on what I think it takes to best explain an event. In certain contexts, (...) optimality and game-theoretic models best explain some central types of evolutionary phenomena. ‡Thanks to Michael Friedman, Helen Longino, Michael Weisberg, and especially Elliott Sober for comments on earlier drafts of this paper. †To contact the author, please write to: Department of Philosophy, Stanford University, Stanford, CA 94305-2155; e-mail: [email protected]. (shrink)

Causal Modeling Semantics (CMS, e.g., Galles and Pearl 1998; Pearl 2000; Halpern 2000) is a powerful framework for evaluating counterfactuals whose antecedent is a conjunction of atomic formulas. We extend CMS to an evaluation of the probability of counterfactuals with disjunctive antecedents, and more generally, to counterfactuals whose antecedent is an arbitrary Boolean combination of atomic formulas. Our main idea is to assign a probability to a counterfactual (A ∨ B) > C at a causal model M as a (...) weighted average of the probability of C in those submodels that truthmake A∨ B (Briggs 2012; Fine 2016, 2017). The weights of the submodels are given by the inverse distance to the original model M, based on a distance metric proposed by Eva, Stern, and Hartmann (2019). Apart from solving a major problem in the epistemology of counterfactuals, our paper shows how work in semantics, causal inference and formal epistemology can be fruitfully combined. (shrink)