The Interrogative Model of Inquiry and Dynamic Epistemic Logics are two central paradigms in formal epistemology. This paper is motivated by the observation of a significant complementarity between them: on the one hand, the IMI provides a framework for investigating inquiry represented as an idealized game between an Inquirer and Nature, along with an account of the interaction between questions and inferences in information-seeking processes, but is lacking a formulation in the multi-agent case; on the other (...) hand, DELs model various operations of information change in multi-agent systems, but the field is lacking a proper integration of question and inference dynamics, along with an application to the investigation of inquiry processes. The goal of this paper is to integrate the two paradigms in such a way as to combine their respective insights. To this end, we develop a formal system called DEL $$_\mathrm{IMI }$$ IMI which aims to represent the interaction between question and inference dynamics in inquiry—as described by the IMI—in a multi-agent setting, and this in such a way as to enable an investigation of inquiry games with multi-agent dimensions. The DEL $$_\mathrm{IMI }$$ IMI system is designed to represent the possible moves of such inquiry games through three types of epistemic actions: agents addressing questions to Nature, agents addressing questions to other agents, agents drawing logical inferences. We then show how the resulting framework can be used to formally define multi-agent inquiry games. We conclude by evaluating the interest of the DEL $$_\mathrm{IMI }$$ IMI system for the IMI and DELs paradigms. (shrink)

Formal dialogue games have been studied in philosophy since at least the time of Aristotle. Recently they have been applied in various contexts in computer science and artificial intelligence, particularly as the basis for interaction between autonomous software agents. We review these applications and discuss the many open research questions and challenges at this exciting interface between philosophy and computer science.

M. B. Hintikka and J. Hintikka claimed that their reconstruction of the ‘Sherlock Holmes sense of deduction’ can “serve as an explication for the link between intelligence and memory”. The claim is vindicated, first for the single-agent case, where the reconstruction captures strategies for accessing the content of a distributed and associative memory; then, for the multi-agent case, where the reconstruction captures strategies for accessing knowledge distributed in a community. Moreover, the reconstruction of the ‘Sherlock Holmes sense (...) of deduction’ allows to conceptualize those strategies as belonging to a continuum of behavioral strategies. (shrink)

Over the last decade, multi-agent systems have come to form one of the key tech- nologies for software development. The Formal Approaches to Multi-Agent Systems (FAMAS) workshop series brings together researchers from the fields of logic, theoreti- cal computer science and multi-agent systems in order to discuss formal techniques for specifying and verifying multi-agent systems. FAMAS addresses the issues of logics for multi-agent systems, formal methods for verification, for example model (...) check- ing, and formal approaches to cooperation, multi-agent planning, communication, coordination, negotiation, games, and reasoning under uncertainty in a distributed environment. In 2007, the third FAMAS workshop, FAMAS'007, was one of the agent workshops gathered together under the umbrella of Multi-Agent Logics, Languages, and Organ- isations - Federated Workshops, MALLOW'007, taking place from 3 to 7 September 2007 in Durham. This current special issue of the Logic Journal of the IGPL gathers together the revised and updated versions of the five best FAMAS'007 contributions. (shrink)

In this paper we revise Reinforcement Learning and adaptiveness in Multi-Agent Systems from an Evolutionary Game Theoretic perspective. More precisely we show there is a triangular relation between the fields of Multi-Agent Systems, Reinforcement Learning and Evolutionary Game Theory. We illustrate how these new insights can contribute to a better understanding of learning in MAS and to new improved learning algorithms. All three fields are introduced in a self-contained manner. Each relation is discussed in detail with (...) the necessary background information to understand it, along with major references to relevant work. (shrink)

Massively multiplayer online games are not merely electronic communication systems based on computational databases, but also include artificial intelligence that possesses complex, dynamic structure. Each visible action taken by a component of the multi-agent system appears simple, but is supported by vastly more sophisticated invisible processes. A rough outline of the typical hierarchy has four levels: interaction between two individuals, each either human or artificial, conflict between teams of agents who cooperate with fellow team members, enduring social-cultural (...) groups that seek to accomplish shared goals, and large-scale cultural traditions, often separated into virtual geographic regions. In many MMOs, both magic and religion are represented, in ways that harmonize with a social-scientific theory that defines them in terms of specific versus general psychological compensators. This article draws empirical examples from five diverse MMOs: Dark Age of Camelot, Dungeons and Dragons Online, World of Warcraft, A Tale in the Desert and Gods and Heroes. (shrink)

In the literature there are at least two main formal structures to deal with situations of interactive epistemology: Kripke models and type spaces. As shown in many papers :149–225, 1999; Battigalli and Siniscalchi in J Econ Theory 106:356–391, 2002; Klein and Pacuit in Stud Log 102:297–319, 2014; Lorini in J Philos Log 42:863–904, 2013), both these frameworks can be used to express epistemic conditions for solution concepts in game theory. The main result of this paper is a formal comparison between (...) the two and a statement of semantic equivalence with respect to two different logical systems: a doxastic logic for belief and an epistemic–doxastic logic for belief and knowledge. Moreover, a sound and complete axiomatization of these logics with respect to the two equivalent Kripke semantics and type spaces semantics is provided. Finally, a probabilistic extension of the result is also presented. A further result of the paper is a study of the relationship between the epistemic–doxastic logic for belief and knowledge and the logic STIT by Belnap and colleagues. (shrink)

The early literature on epistemic logic in philosophy focused on reasoning about the knowledge or belief of a single agent, especially on controversies about "introspection axioms" such as the 4 and 5 axioms. By contrast, the later literature on epistemic logic in computer science and game theory has focused on multi-agent epistemic reasoning, with the single-agent 4 and 5 axioms largely taken for granted. In the relevant multi-agent scenarios, it is often important to reason (...) about what agent A believes about what agent B believes about what agent A believes; but it is rarely important to reason just about what agent A believes about what agent A believes. This raises the question of the extent to which single-agent introspection axioms actually matter for multi-agent epistemic reasoning. In this paper, we formalize and answer this question. To formalize the question, we first define a set of multi-agent formulas that we call agent-alternating formulas, including formulas like Box_a Box_b Box_a p but not formulas like Box_a Box_a p. We then prove, for the case of belief, that if one starts with multi-agent K or KD, then adding both the 4 and 5 axioms (or adding the B axiom) does not allow the derivation of any new agent-alternating formulas—in this sense, introspection axioms do not matter. By contrast, we show that such conservativity results fail for knowledge and multi-agent KT, though they hold with respect to a smaller class of agent-nonrepeating formulas. (shrink)

The situation calculus is a logical formalism that has been extensively developed for planning. We apply the formalism in a complex multi-agent domain, modelled on the game of Clue. We find that the situation calculus, with suitable extensions, supplies a unified representation of (1) the interaction protocol, or structure of the game, (2) the dynamics of the knowledge and common knowledge of the agents, and (3) principles of strategic planning.

Co-learning of multiple agents has been studied in co-learning settings, and how do they help, or many different disciplines under various guises. For hamper, learning and cooperation? example, the issue has been tackled by distributed • How do we characterize the process and the artificial intelligence, parallel and distributed com- dynamics of co-learning, conceptually, mathe- puting, cognitive psychology, social psychology, matically, or computationally? game theory (and other areas of mathematical econ- • how do social structures and relations interact omics), sociology, (...) anthropology, and many other with co-learning of multiple agents? related disciplines. (shrink)

We draw parallels between several closely related logics that combine — in different proportions — elements of game theory, computation tree logics, and epistemic logics to reason about agents and their abilities. These are: the coalition game logics CL and ECL introduced by Pauly 2000, the alternating-time temporal logic ATL developed by Alur, Henzinger and Kupferman between 1997 and 2002, and the alternating-time temporal epistemic logic ATEL by van der Hoek and Wooldridge (2002). In particular, we establish some subsumption and (...) equivalence results for their semantics, as well as interpretation of the alternating-time temporal epistemic logic into ATL. The focus in this paper is on models: alternating transition systems, multi-player game models (alias concurrent game structures) and coalition effectivity models turn out to be intimately related, while alternating epistemic transition systems share much of their philosophical and formal apparatus. Our approach is constructive: we present ways to transform between different types of models and languages. (shrink)

I present a game-theoretical multi-agent system to simulate the evolutionary process responsible for the pragmatic phenomenon division of pragmatic labour (DOPL), a linguistic convention emerging from evolutionary forces. Each agent is positioned on a toroid lattice and communicates via signaling games , where the choice of an interlocutor depends on the Manhattan distance between them. In this framework I compare two learning dynamics: reinforcement learning (RL) and belief learning (BL). An agent’s experiences from previous plays (...) influence his communication behaviour, and RL agents act in a non-rational way whereas BL agents display a small degree of rationality by using best response dynamics . The complete system simulates an evolutionary process of communication strategies, which agents can learn in a structured spatial society. The significant questions are: what circumstances could lead to an evolutionary process that doesn’t result in the expected DOPL convention; and to what extent is interlocutor rationality necessary for the emergence of a society-wide convention à la DOPL? (shrink)

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

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

If there is one aspect of David Gauthier's program for a contractualist morality that has been most sceptically received, it is his view that instrumentally rational agents would choose to adopt a disposition that would in turn constrain their future choices. Instead of remaining “straightforward maximizers” caught in a suboptimal state of nature, they would become “constrained maximizers” who could avoid prisoner's dilemmas by engaging in conditional co-operation. Apart from the fact that Gauthier's entirely prescriptive orientation leads him to omit (...) any specification of the mechanism through which this might be accomplished, serious doubts have been raised about the adequacy of the argument that he offers in support of adopting constrained maximization. (shrink)

We develop a multi-agent deontic action logic to study the logical behaviour of two types of deontic conditionals: (1) conditional obligations, having the form "If group H were to perform action aH, then, in group F's interest, group G ought to perform action aG" and (2) conditional permissions, having the form "If group H were to perform action aH, then, in group F's interest, group G may perform action aG". First, we define a formal language for multi- (...) class='Hi'>agent deontic action logic and a class of consequentialist models to interpret the formulas of the language. Second, we define a transformation that converts any strategic game into a consequentialist model. Third, we show that an outcome a* is a Nash equilibrium of a strategic game if and only if a conjunction of certain conditional permissions is true in the consequentialist model that results from the transformation of that strategic game. (shrink)

This chapter takes inspiration from Wittgenstein’s thinking to formulate a non-reductive toolbox for the study of religion associated with generative modelling, specifically as applied in complex adaptive systems theory. It converges on a communal perspective on religion as multiscale active inference that contrasts starkly with common ‘straw person’ perspectives on religion that reduce it to ‘erroneous’ theorising generated by the brain. In contrast, we argue, religious practices at the enculturated level of description involve implicit and explicit meanings, experienced both individually (...) and collectively. Firstly, we characterise these in terms of Wittgenstein’s notions of rule-following and language games. Secondly, we discuss how the collective and perspectival aspects of religion in enculturation with morals, doctrines, rituals, and expressions can be formalised in terms of deep active inference in multi-agent systems. This approach describes how religions are incommensurable with scientific methods due to the epistemic separation between the different kinds of language games of religious and scientific practices. Their touchpoints tend to give rise to perpetual confusion and unproductive discussions, requiring perspicuous presentations that can be formulated with our toolbox. In this sense, our account has implications for tackling complex societal challenges such as ethical policy-making. (shrink)

Causal reasoning and game-theoretic reasoning are fundamental topics in artificial intelligence, among many other disciplines: this paper is concerned with their intersection. Despite their importance, a formal framework that supports both these forms of reasoning has, until now, been lacking. We offer a solution in the form of (structural) causal games, which can be seen as extending Pearl's causal hierarchy to the game-theoretic domain, or as extending Koller and Milch's multi-agent influence diagrams to the causal domain. We (...) then consider three key questions: i) How can the (causal) dependencies in games - either between variables, or between strategies - be modelled in a uniform, principled manner? ii) How may causal queries be computed in causal games, and what assumptions does this require? iii) How do causal games compare to existing formalisms? To address question i), we introduce mechanised games, which encode dependencies between agents' decision rules and the distributions governing the game. In response to question ii), we present definitions of predictions, interventions, and counterfactuals, and discuss the assumptions required for each. Regarding question iii), we describe correspondences between causal games and other formalisms, and explain how causal games can be used to answer queries that other causal or game-theoretic models do not support. Finally, we highlight possible applications of causal games, aided by an extensive open-source Python library. (shrink)

Understanding the flow of knowledge in multi-agent protocols is essential when proving the correctness or security of such protocols. Current logical approaches, often based on model checking, are well suited for modeling knowledge in systems where agents do not act strategically. Things become more complicated in strategic settings. In this paper we show that such situations can be understood as a special type of game – a knowledge condition game – in which a coalition “wins” if it is (...) able to bring about some epistemic condition. This paper summarizes some results relating to these games. Two proofs are presented for the computational complexity of deciding whether a coalition can win a knowledge condition game with and without opponents (Σ2P-complete and NP-complete respectively). We also consider a variant of knowledge condition games in which agents do not know which strategies are played, and prove that under this assumption, the presence of opponents does not affect the complexity. The decision problem without opponents is still NP-complete, but requires a different proof. (shrink)

Sequential von Neumann–Morgernstern (VM) games are a very general formalism for representing multi-agent interactions and planning problems in a variety of types of environments. We show that sequential VM games with countably many actions and continuous utility functions have a sound and complete axiomatization in the situation calculus. This axiomatization allows us to represent game-theoretic reasoning and solution concepts such as Nash equilibrium. We discuss the application of various concepts from VM game theory to the theory (...) of planning and multi-agent interactions, such as representing concurrent actions and using the Baire topology to define continuous payoff functions. (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.

Understanding the flow of knowledge in multi-agent protocols is essential when proving the correctness or security of such protocols. Current logical approaches, often based on model checking, are well suited for modeling knowledge in systems where agents do not act strategically. Things become more complicated in strategic settings. In this paper we show that such situations can be understood as a special type of game – a knowledge condition game – in which a coalition “wins” if it is (...) able to bring about some epistemic condition. This paper summarizes some results relating to these games. Two proofs are presented for the computational complexity of deciding whether a coalition can win a knowledge condition game with and without opponents (Σ2P-complete and NP-complete respectively). We also consider a variant of knowledge condition games in which agents do not know which strategies are played, and prove that under this assumption, the presence of opponents does not affect the complexity. The decision problem without opponents is still NP-complete, but requires a different proof. (shrink)

A general game player automatically learns to play arbitrary new games solely by being told their rules. For this purpose games are specified in the general Game Description Language (GDL), a variant of Datalog with function symbols that uses a few game-specific keywords. A recent extension of basic GDL allows the description of nondeterministic games with any number of players who may have incomplete, asymmetric information. In this paper, we analyse the epistemic structure and expressiveness of this (...) language in terms of modal epistemic logic and prove two main results: (1) The operational semantics of GDL entails that the situation at any stage of a game can be characterised by a multi-agent epistemic (i.e., S5-) model; (2) GDL is sufficiently expressive to model any situation that can be described by a (finite) multi-agent epistemic model. (shrink)

Many problems in Multi-Agent Systems (MASs) research are formulated in terms of the abilities of a coalition of agents. Existing approaches to reasoning about coalitional ability are usually focused on games or transition systems, which are described in terms of states and actions. Such approaches however often neglect a key feature of multi-agent systems, namely that the actions of the agents require resources. In this paper, we describe a logic for reasoning about coalitional ability under (...) resource constraints in the probabilistic setting. We extend Resource-bounded Alternating-time Temporal Logic (RB-ATL) with probabilistic reasoning and provide a standard algorithm for the model-checking problem of the resulting logic Probabilistic resource-bounded ATL (pRB-ATL). We implement model-checking algorithms and present experimental results using simple multi-agent model-checking problems of increasing complexity. (shrink)

The purpose of this paper is to present a formal model of social net- works suitable for studying questions in social epistemology. We show how to use this model, in conjunction with a computer program for simulating groups of inquirers, to draw conclusions about the epistemological prop- erties of different social practices. This furnishes us with the beginnings of a systematic research program in social epistemology, from which to approach problems pertaining to epistemic value, optimal organization, and the dynamics of (...) multi-agent inquiry. (shrink)

In studies of multi-agent interaction, especially in game theory, the notion of equilibrium often plays a prominent role. A typical scenario for the belief merging problem is one in which several agents pool their beliefs together to form a consistent "group" picture of the world. The aim of this paper is to define and study new notions of equilibria in belief merging. To do so, we assume the agents arrive at consistency via the use of a social belief (...) removal function, in which each agent, using his own individual removal function, removes some belief from his stock of beliefs. We examine several notions of equilibria in this setting, assuming a general framework for individual belief removal due to Booth et al. We look at their inter-relations as well as prove their existence or otherwise. We also show how our equilibria can be seen as a generalisation of the idea of taking maximal consistent subsets of agents. (shrink)

What is it that evolves in cultural evolution? This is a question easily posed but not so easily answered. According to common interpretations of cultural evolutionary theory, it is not strictly agents that change over time or proliferate during cultural transmission, but their socially transmitted behavior, what they communicate or acquire via social learning – in short: their interactions. This means that we have to put these cultural interactions into an evolutionary setting and show how they evolve within cultural populations, (...) i.e. within social networks. But the social networks themselves also evolve, which brings us to a multi-level approach of cultural evolution, implementing both, individual and group selection. In this paper I will assume that the microlevel is given by a description of cultural agents, their behavior and decisions, whereas the macrolevel describes the dynamics on population structure and in particular population boundaries in social networks (since we are not really able to identify something analogous to ‘species’ in cultural evolution). In this paper, I am going to offer a specific mathematical model, that makes use of game theory for representing the cultural microlevel and graph theory for the cultural macrolevel. It has to be shown, how both can formally be linked in a synthetic attempt. (shrink)

Contents: Matti SINTONEN: From the Science of Logic to the Logic of Science. I: HISTORICAL PERSPECTIVES. Zev BECHLER: Hintikka on Plenitude in Aristotle. Marja-Liisa KAKKURI-KNUUTTILA: What Can the Sciences of Man Learn from Aristotle? Martin KUSCH: Theories of Questions in German-Speaking Philosophy Around the Turn of the Century. Nils-Eric SAHLIN: 'HE IS NO GOOD FOR MY WORK': On the Philosophical Relations between Ramsey and Wittgenstein. II: FORMAL TOOLS: INDUCTION, OBSERVATION AND IDENTIFIABILITY. Theo A.F. KUIPERS: The Carnap-Hintikka Programme in Inductive Logic. (...) Isaac LEVI: Caution and Nonmonotonic Inference. Ilkka NIINILUOTO: Inductive Logic, Atomism, and Observational Error. Arto MUTANEN: Theory of Identifiability. III: QUESTIONS IN INQUIRY: THE INTERROGATIVE MODEL. Sylvain BROMBERGER: Natural Kinds and Questions. Scott A. KLEINER: The Structure of Inquiry in Developmental Biology. Andrzej WISNIEWSKI: Some Foundational Concepts of Erotetic Semantics. Jan WOLE??N??SKI: Science and Games. IV: GROWTH OF KNOWLEDGE: EXPLANATION AND DISCOVERY. Matti SINTONEN: Explanation: The Fifth Decade. Erik WEBER: Scientific Explanation and the Interrogative Model of Inquiry. George GEBHARD: Scientific Discovery, Induction, and the Multi-Level Character of Scientific Inquiry. Mika KIIKERI: On the Logical Structure of Learning Models. V: JAAKKO HINTIKKA: REPLIES. VI: ABSTRACTS. (shrink)

Dung’s argumentation frameworks have been applied for over twenty years to the analysis of argument justification. This representation focuses on arguments and the attacks among them, abstracting away from other features like the internal structure of arguments, the nature of utterers, the specifics of the attack relation, etc. The model is highly attractive because it reduces most of the complexities involved in argumentation processes. It can be applied to different settings, like the argument evaluation of an individual agent or (...) the case of dialectic disputes between two agents (pro and con), or even in multi-agent collective argumentation. The latter case involves agents with possibly different arguments and/or opinions on how to evaluate them, leading to the possibility of considering multiple sets of arguments and attack relations. Two basic questions can be asked here, namely ‘what to aggregate’ and ‘how to aggregate’. The former concerns what kinds of entities do the agents intend to choose (arguments, attacks, assessments, etc.), while the second one focuses on which aggregation mechanisms yield rational choices (voting on arguments, merging procedures to obtain a common argumentation framework, deliberation processes, etc.). In particular, the question about the rationality of a collective argument choice relates this topic to Social Choice and Judgment Aggregation theories, while its associated strategic issues relate it to Game Theory. The research efforts on the disparate problems elicited by collective argumentation have generated a considerable corpus of literature that deserves an orderly evaluation. This survey is intended as a contribution to that end. (shrink)

This study analyses behaviour in non-zero-sum finite multi-stage games, particularly the Centipede Game. The classical Nash Equilibrium fails to explain empirical behaviour and intuitive logic and has therefore been challenged. This paper introduces the ‘Pure Collective Equilibrium’, or PCE, which describes the equilibrium reached when agents assess their utility not by their own payoffs but by the mean collective payoff of the team, as outlined by some team-reasoning hypotheses. Classical behaviour and purely collective team reasoning then both represent (...) special cases—the first in which agents and their counterparts are on the Nash Equilibrium path, and the second in which agents and their counterparts are purely collective team reasoners. It is argued that agents intentionally and consistently deviate from classical rationality in the Centipede Game, even in the absence of philanthropic altruists or error-plagued populations. (shrink)

From its inception, philosophy for/with children (P4wC) has sought to promote philosophical discussion with children based on the latter’s own questions and a pedagogic method designed to encourage critical, creative, and caring thinking. Communities of inquiry can be plagued by power struggles prompted by diverse identities, however. These not always being highlighted in the literature or P4wC discourse, this article proposes a two-stage model for facilitators as part of their ethical responsibility. In the first phase, they should free themselves (...) from assumptions and closed-mindedness. They should liberate themselves from pedagogy of fear and “banking education” in order to act freely in an educational space characterized by improvisation that cultivates participation of the children. Here, the text is based on normalizing education principles, counter-education and diasporic-education approaches in order to ensure openness and inclusiveness. In the second, they should embrace enabling-identity views and practices in order to make the community of inquiry as identity-broad and -rich as possible, recognizing and legitimizing the participants’ differences. Here, the text is based on principles such as recognizing power games as part of the community, ensuring multi-narratives human environment and enabling epistemic justice in order to ensure perspectival multiplicity, multiple identities, and the legitimization of difference characterized by pedagogy of search. (shrink)

Research in multi-agent systems typically assumes a regulative model of social practice. This model starts with agents who are already capable of acting autonomously to further their individual ends. A social practice, according to this view, is a way of achieving coordination between multiple agents by restricting the set of actions available. For example, in a world containing cars but no driving regulations, agents are free to drive on either side of the road. To prevent collisions, we introduce (...) driving regulations, insisting that everyone drives on the left hand side of the road. We accept this limitation on our freedom because it lowers the probability of a collision. -/- This paper describes AI systems that are based on the constitutive view of social practice. According to this alternative view, there are certain actions that are only available to the agent because he is participating in a practice of a certain sort. For example, you can swing a peculiarly shaped piece of wood without participating in any particular practice - but this action will only constitute a strike if you are participating in a game of baseball. I can raise my hand whenever I like, but this only counts as voting for the motion within the institution of voting. But not all the examples are from frivolous, optional or institutional activities. Sellars and Brandom argue that even the fundamental act of assertion is only possible within the context of a particular social practice: the Game of Giving and Asking for Reasons. -/- The constitutive view, which is familiar to philosophers, is relatively unknown within the AI community. -/- The central aim of this paper is to show how the constitutive view of practice can be put to use in AI applications. (shrink)

This book focuses on the problem of responsibility voids: these are cases where responsibility for a morally undesirable outcome cannot be attributed to any of the involved agents. Responsibility voids are thought to occur in collective decision-making and in the context of artificial intelligent systems. In these cases, philosophers worry that there is a shortfall of moral responsibility. In particular, such voids are often assumed to justify a notion of collective responsibility that cannot be reduced to individual responsibility. One of (...) the aims of the book is to study how collective responsibility and joint action relate to individual responsibility and individual actions. The book offers a unifying framework for modelling moral responsibility by drawing from modal logic and game theory. -/- The book investigates the possibility and scope of the problem of responsibility voids. One of its characteristics is its pluralistic perspective on moral responsibility: in contrast to giving a unique and all-encompassing definition of it, the book makes progress by spelling out and modelling several conceptions of moral responsibility. One of the appealing features of the book is that a relatively small range of models is used to investigate a variety of conceptions of moral responsibility. The unifying framework can thus be used to characterize the conditions under which responsibility voids are ruled out. (shrink)

In earlier work, I have presented an interpretation of Obligationes as logical games of consistency maintenance; this interpretation has some advantages, in particular that of capturing the multi-agent, goal-oriented, rule-governed nature of the enterprise by means of the game analogy. But it has as its main limitation the fact that it does not provide a satisfactory account of the deontic aspect of the framework—i.e. of what being obliged to a certain statement consists in. In order to remedy (...) this shortcoming, this paper argues for the more encompassing thesis that Obligationes can be viewed as a theory of rational dialogical practices, in particular concerning the management of one's discursive commitments. The main inspiration for this interpretation comes from R. Brandom's inferentialist, normative pragmatism, but more generally, it relies heavily on a dialogical conception of logic. I argue that it offers a more compelling account of several aspects of the obligational framework, in particular the role of doubting responses and the ubiquity of obligational vocabulary in the context of scientific discourse in the medieval tradition. (shrink)

Current dynamic epistemic logics for analyzing effects of informational events often become cumbersome and opaque when common knowledge is added for groups of agents. Still, postconditions involving common knowledge are essential to successful multi-agent communication. We propose new systems that extend the epistemic base language with a new notion of ‘relativized common knowledge’, in such a way that the resulting full dynamic logic of information flow allows for a compositional analysis of all epistemic postconditions via perspicuous ‘reduction axioms’. (...) We also show how such systems can deal with factual alteration, rather than just information change, making them cover a much wider range of realistic events. After a warm-up stage of analyzing logics for public announcements, our main technical results are expressivity and completeness theorems for a much richer logic that we call LCC. This is a dynamic epistemic logic whose static base is propositional dynamic logic (PDL), interpreted epistemically. This system is capable of expressing all model-shifting operations with finite action models, while providing a compositional analysis for a wide range of informational events. This makes LCC a serious candidate for a standard in dynamic epistemic logic, as we illustrate by analyzing some complex communication scenarios, including sending successive emails with both ‘cc’ and ‘bcc’ lines, and other private announcements to subgroups. Our proofs involve standard modal techniques, combined with a new application of Kleene’s theorem on finite automata, as well as new Ehrenfeucht games of model comparison. (shrink)

The aim of this paper, is to provide a logical framework for reasoning about actions, agency, and powers of agents and coalitions in game-like multi-agent systems. First we define our basic Dynamic Logic of Agency ( ). Differently from other logics of individual and coalitional capability such as Alternating-time Temporal Logic (ATL) and Coalition Logic, in cooperation modalities for expressing powers of agents and coalitions are not primitive, but are defined from more basic dynamic logic operators of action (...) and (historic) necessity. We show that STIT logic can be reconstructed in . We then extend with epistemic operators, which allows us to distinguish capability and power. We finally characterize the conditions under which agents are aware of their capabilities and powers. (shrink)

The papers collected in this volume exemplify some of the trends in current approaches to logic, language and computation. Written by authors with varied academic backgrounds, the contributions are intended for an interdisciplinary audience. The first part of this volume addresses issues relevant for multi-agent systems: reasoning with incomplete information, reasoning about knowledge and beliefs, and reasoning about games. Proofs as formal objects form the subject of Part II. Topics covered include: contributions on logical frameworks, linear logic, (...) and different approaches to formalized reasoning. Part III focuses on representations and formal methods in linguistic theory, addressing the areas of comparative and temporal expressions, modal subordination, and compositionality. (shrink)

Folk ontology seems baroque, compared to the austere ontology of many philosophers. Plausibly, the issue comes down to a choice between existence concepts: the folk and the austere philosophers employ different quantifier meanings. This paper aims to clarify and defend this hypothesis and explore its upshots. How do we choose between the alternative existence concepts; is the austere philosophers’ concept better than the folk’s undiscriminating one? I will argue that contrary to what Ted Sider suggests, the austere existence concept and (...) the corresponding austere answers to existence questions do not prevail in the context of “inquiry”, i.e. the context of practically disinterested pursuit of epistemic excellence. Sider’s suggestion relies on a one-sided idea of epistemic excellence, as beliefs’ conforming to the world. Once we recognize another epistemic aim, namely the agent understanding connections between known facts, ordinary objects will be back in the game. (shrink)

The article outlines the prospects of using J. Hintikka’s interrogative epistemology for modelling cognitive operations carried out by a cognizing agent to create a machine capable of full cognition. It was established that modeling is divided into two objectives: modeling the cognitive operations and modeling the strategic reasoning. Interrogative epistemology presents a solution to the first objective. It relies on a game-theoretic formal apparatus that allows one to correctly describe all types of possible moves within the framework of a (...) particular cognitive game. The second objective cannot be accomplished in a general epistemological theory framework since strategic considerations about the organization of research and even the concept of knowledge inevitably depend on the broader context of an agent’s practical activity. Therefore, interrogative epistemology does not claim a universal and complete description of the process of cognition, focusing on other tasks: primarily on identifying hidden premises that cognitive agents use in their reasoning. For the same reason, interrogative epistemology deems the possibility of the existence of a cognizing machine as formally unsubstantiated and questionable. However, arguments are given in favor of the fact that interrogative epistemology serves as an acceptable conceptual framework for clarifying the nature of the difficulties that arise with attempts to accomplish the second objective and improving the quality of philosophical discourse in the field of artificial intelligence research. The author substantiates this position by arguing that the ability to cognize presupposes the ability to perform all the essential functions that are usually called mental. (shrink)

Many logical systems today describe intelligent interacting agents over time. Frameworks include Interpreted Systems (IS, Fagin et al. [8]), Epistemic-Temporal Logic (ETL, Parikh & Ramanujam [22]), STIT (Belnap et al. [5]), Process Algebra and Game Semantics (Abramsky [1]). This variety is an asset, as different modeling tools can be fine-tuned to specific applications. But it may also be an obstacle, when barriers between paradigms and schools go up. This paper takes a closer look at one particular interface, between two systems (...) that both address the dynamics of knowledge and information flow in multi-agent systems. One is IS/ETL (IS and ETL are, from a technical point of view, the same up to model transformations, cf. [20]), which uses linear or branching time models with added epistemic structure induced by agents’ different capabilities for observing events. These models provide a Grand Stage where histories of some process unfold constrained by a protocol, and a matching epistemic-temporal language describes what happens. The other framework is Dynamic Epistemic Logic (DEL, [10, 4, 34]) that describes interactive processes in terms of epistemic event models which may occur inside modalities of the language. Temporal evolution is then computed from some initial epistemic model through a process of successive ‘product updates’. It has long been unclear how to best compare IS/ETL and DEL. Various aspects have been investigated in [10, 30, 32], but in this paper, we study the interface in a more systematic way. Often, DEL and ETL are presented as alternative ways of adding dynamics to multi-agent epistemic models. In this paper, we rather focus on how merging the two different modeling choices leads to interesting new questions. Our leading interest here will be a view of informational processes as evolving over time. To see what we mean, consider the simplest version of DEL, viz. the logic of public announcements PAL ([23]) which adds a very specific type of communicative 1 action to epistemic models: a public announcement.. (shrink)

The COVID-19 pandemic poses a major challenge to policy makers on how to encourage compliance to social distancing and personal protection rules. This paper compares the effectiveness of two policies that aim to increase the frequency of responsible health behavior using smartphone-tracking applications. The first involves enhanced alert capabilities, which remove social externalities and protect the users from others’ reckless behavior. The second adds a rule enforcement mechanism that reduces the users’ benefit from reckless behavior. Both strategies should be effective (...) if agents are expected-value maximizers, risk averse, and behave in accordance with cumulative prospect theory or in accordance with the Cognitive Hierarchy model. A multi-player trust-game experiment was designed to compare the effectiveness of the two policies. The results reveal a substantial advantage to the enforcement application, even one with occasional misses. The enhanced-alert strategy was completely ineffective. The findings align with the small samples hypothesis, suggesting that decision makers tend to select the options that lead to the best payoff in a small sample of similar past experiences. In the current context, the tendency to rely on a small sample appears to be more consequential than other deviations from rational choice. (shrink)

Miyagawa (Games and Economics Behavior 41(2), 292–308 [2002]) provides a simple extensive game form that implements a large class of two-agent bargaining solutions in subgame-perfect equilibrium. This class includes all of the Nash, Kalai–Smorodinsky, and relative utilitarian solutions. This note extends Miyagawa’s result to multi-agent bargaining problems.

The cognitive hierarchy model is an approach to decision making in multi-agent interactions motivated by laboratory studies of people. It bases decisions on empirical assumptions about agents’ likely play and agents’ limited abilities to second-guess their opponents. It is attractive as a model of human reasoning in economic settings, and has proved successful in designing agents that perform effectively in interactions not only with similar strategies but also with sophisticated agents, with simpler computer programs, and with people. In (...) this paper, we explore the qualitative structure of iterating best response solutions in two repeated games, one without messages and the other including communication in the form of non-binding promises and threats. Once the model anticipates interacting with sufficiently sophisticated agents with a sufficiently high probability, reasoning leads to policies that disclose intentions truthfully, and expect credibility from the agents they interact with, even as those policies act aggressively to discover and exploit other agents’ weaknesses and idiosyncrasies. Non-binding communication improves overall agent performance in our experiments. (shrink)

To depict the mechanisms that have enabled the emergence of semantic conventions, philosophers and researchers particularly access a game-theoretic model: the signaling game. In this article I argue that this model is also quite appropriate to analyze not only the emergence of a semantic convention, but also its change. I delineate how the application of signaling games helps to reproduce and depict mechanisms of semantic change. For that purpose I present a model that combines a signaling game with innovative (...) reinforcement learning; in simulation runs I conduct this game repeatedly within a multi-agent setup, where agents are arranged in social network structures. The results of these runs are contrasted with an attested theory from sociolinguistics: the ‘weak tie’ theory. Analyses of the produced data target a deeper understanding of the role of environmental variables for the promotion of semantic change or solidity of semantic conventions. (shrink)

Contemporary epistemological and cognitive studies, as well as recent trends in computer science and game theory have revealed an increasingly important and intimate relationship between Information, Interaction, and Agency. Agents perform actions based on the available information and in the presence of other interacting agents. From this perspective Information, Interaction, and Agency neatly ties together classical themes like rationality, decision-making and belief revision with games, strategies and learning in a multi-agent setting. Unified by the central notions Information, (...) Interaction, and Agency, the essays in this volume provide refreshing methodological perspectives on belief revision, dynamic epistemic logic, von Neumann games, and evolutionary game theory; all of which in turn are central approaches to understanding our own rationality and that of other agents. (shrink)

This book illustrates the program of Logical-Informational Dynamics. Rational agents exploit the information available in the world in delicate ways, adopt a wide range of epistemic attitudes, and in that process, constantly change the world itself. Logical-Informational Dynamics is about logical systems putting such activities at center stage, focusing on the events by which we acquire information and change attitudes. Its contributions show many current logics of information and change at work, often in multi-agent settings where social behavior (...) is essential, and often stressing Johan van Benthem's pioneering work in establishing this program. However, this is not a Festschrift, but a rich tapestry for a field with a wealth of strands of its own. The reader will see the state of the art in such topics as information update, belief change, preference, learning over time, and strategic interaction in games. Moreover, no tight boundary has been enforced, and some chapters add more general mathematical or philosophical foundations or links to current trends in computer science. (shrink)

This paper presents a GA-based multi-agent reinforce- ment learning bidding approach (GMARLB) for perform- ing multi-agent reinforcement learning. GMARLB inte- grates reinforcement learning, bidding and genetic algo- rithms. The general idea of our multi-agent systems is as follows: There are a number of individual agents in a team, each agent of the team has two modules: Q module and CQ module. Each agent can select actions to be performed at each step, which (...) are done by the Q module. While the CQ module determines at each step whether the agent should continue or relinquish control. Once an agent relinquishes its control, a new agent is selected by bidding algorithms. We applied GA-based GMARLB to the Backgammon game. The experimental results show GMARLB can achieve a su- perior level of performance in game-playing, outperforming PubEval, while the system uses zero built-in knowledge. (shrink)

This paper argues that chance (risk or opportunity) discovery is challenging, from a reasoning point of view, because it represents a dilemma for inductive reasoning. Chance discovery shares many features with the grue paradox. Consequently, Bayesian approaches represent a potential solution. The Bayesian solution evaluates alternative models generated using a temporal logic planner to manage the chance. Surprise indices are used in monitoring the conformity of the real world and the assessed probabilities. Game theoretic approaches are proposed to deal with (...) multi-agent interaction in chance management. (shrink)