One of the major problems that artificial intelligence needs to tackle is the combination of different and potentially conflicting sources of information. Examples are multi-sensor fusion, database integration and expert systems development. In this paper we are interested in the aggregation of propositional logic-based information, a problem recently addressed in the literature on information fusion. It has applications in multi-agent systems that aim at aggregating the distributed agent-based knowledge into an (ideally) unique set of propositions. (...) We consider a group of autonomous agents who individually hold a logically consistent set of propositions. Each set of propositions represents an agent’s beliefs on issues on which the group has to make a collective decision. To make the collective decision, several aggregation procedures have been proposed in the literature. Assuming that all propositions in question are factually right or wrong, we ask how good belief fusion is as a truth tracker. Will it single out the true set of propositions? And how does information fusion compare with other aggregation procedures? We address these questions in a probabilistic framework and show that information fusion does especially well for agents with a middling competence of hitting the truth of an individual proposition. (shrink)

This paper proposes a Multi-Agent based Particle Swarm Optimization (PSO) Framework for the Traveling salesman problem (MAPSOFT). The framework is a deployment of the recently proposed intelligent multi-agent based PSO model by the authors. MAPSOFT is made up of groups of agents that interact with one another in a coordinated search effort within their environment and the solution space. A discrete version of the original multi-agent model is presented and applied to the Travelling Salesman (...) Problem. Based on the simulation results obtained, it was observed that agents retrospectively decide on their next moves based on consistent better fitness values obtained from present and prospective neighborhoods, and by reflecting back to previous behaviors and sticking to historically better results. These overall attributes help enhance the conventional PSO by providing more intelligence and autonomy within the swarm and thus contributed to the emergence of good results for the studied problem. (shrink)

In this paper, we study the evolution of knowledge in multi-agent conformant planning over transition systems. We propose a dynamic epistemic logical framework with modalities of distributed knowledge to handle the epistemic reasoning in such scenarios, and we reduce a problem of multi-agent conformant planning to a model checking problem. We prove that multi-agent conformant planning is Pspace-complete on the size of the dynamic epistemic model.

Argument evaluation, one of the central problems in argumentation theory, consists in studying what makes an argument a good one. This paper proposes a formal approach to argument evaluation from the perspective of justification logic. We adopt a multi-agent setting, accepting the intuitive idea that arguments are always evaluated by someone. Two general restrictions are imposed on our analysis: non-deductive arguments are left out and the goal of argument evaluation is fixed: supporting a given proposition. Methodologically, our (...) approach uses several existing tools borrowed from justification logic, awareness logic, doxastic logic and logics for belief dependence. We start by introducing a basic logic for argument evaluation, where a list of argumentative and doxastic notions can be expressed. Later on, we discuss how to capture the mentioned form of argument evaluation by defining a preference operator in the object language. The intuitive picture behind this definition is that, when assessing a couple of arguments, the agent puts them to a test consisting of several criteria. As a result of this process, a preference relation among the evaluated arguments is established by the agent. After showing that this operator suffers a special form of logical omniscience, called preferential omniscience, we discuss how to define an explicit version of it, more suitable to deal with non-ideal agents. The present work exploits the formal notion of awareness in order to model several informal phenomena: awareness of sentences, availability of arguments and communication between agents and external sources. We discuss several extensions of the basic logic and offer completeness and decidability results for all of them. (shrink)

In this paper, we propose a dynamic epistemic framework to capture the knowledge evolution in multi-agent systems where agents are not able to observe. We formalize multi-agent conformant planning with group knowledge, and reduce planning problems to model checking problems. We prove that multi-agent conformant planning with group knowledge is Pspace -complete on the size of dynamic epistemic models. We also consider the alternative Kripke semantics, and show that for each Kripke model (...) with perfect recall and no miracles, there is an equivalent dynamic epistemic model and vice versa. (shrink)

Collaboration requires agents to coordinate their behavior on the fly, sometimes cooperating to solve a single task together and other times dividing it up into sub‐tasks to work on in parallel. Underlying the human ability to collaborate is theory‐of‐mind (ToM), the ability to infer the hidden mental states that drive others to act. Here, we develop Bayesian Delegation, a decentralized multi‐agent learning mechanism with these abilities. Bayesian Delegation enables agents to rapidly infer the hidden intentions of others by (...) inverse planning. We test Bayesian Delegation in a suite of multi‐agent Markov decision processes inspired by cooking problems. On these tasks, agents with Bayesian Delegation coordinate both their high‐level plans (e.g., what sub‐task they should work on) and their low‐level actions (e.g., avoiding getting in each other's way). When matched with partners that act using the same algorithm, Bayesian Delegation outperforms alternatives. Bayesian Delegation is also a capable ad hoc collaborator and successfully coordinates with other agent types even in the absence of prior experience. Finally, in a behavioral experiment, we show that Bayesian Delegation makes inferences similar to human observers about the intent of others. Together, these results argue for the centrality of ToM for successful decentralized multi‐agent collaboration. (shrink)

In this paper, we investigate the use of event models for automated planning. Event models are the action defining structures used to define a semantics for dynamic epistemic logic. Using event models, two issues in planning can be addressed: Partial observability of the environment and knowledge. In planning, partial observability gives rise to an uncertainty about the world. For single-agent domains, this uncertainty can come from incomplete knowledge of the starting situation and from the nondeterminism of actions. In (...) class='Hi'>multi-agent domains, an additional uncertainty arises from the fact that other agents can act in the world, causing changes that are not instigated by the agent itself. For an agent to successfully construct and execute plans in an uncertain environment, the most widely used formalism in the literature on automated planning is “belief states”: sets of different alternatives for the current state of the world. Epistemic logic is a significantly more expressive and theoretically better founded method for representing knowledge and ignorance about the world. Further, epistemic logic allows for planning according to the knowledge (and iterated knowledge) of other agents, allowing the specification of a more complex class of planning domains, than those simply concerned with simple facts about the world. We show how to model multi-agent planning problems using Kripke-models for representing world states, and event models for representing actions. Our mechanism makes use of slight modifications to these concepts, in order to model the internal view of agents, rather than that of an external observer. We define a type of planning domain called epistemic planning domains, a generalisation of classical planning domains, and show how epistemic planning can successfully deal with partial observability, nondeterminism, knowledge and multiple agents. Finally, we show epistemic planning to be decidable in the single-agent case, but only semi-decidable in the multi-agent case. (shrink)

The emergence of new technologies such as the Internet of things and the Cloud transforms the way we interact. Whether it be human to human interaction or human to machine interaction, the size of the networks keeps growing. As the networks get more complex nowadays with many interconnected components, it is necessary to develop distributed scalable algorithms so as to minimize the computation required in decision making in such large-scale systems. In this paper, we consider a setup where each (...) class='Hi'>agent in the network updates its opinion by relying on its neighbors’ opinions. The information exchange between the agents is assumed to be mutual. The cluster consensus problem is investigated for networks represented by static or time-varying graphs. Joint and integral connectivity conditions are utilized to determine the number of clusters that are formed, as the interactions among the agents evolve over time. Finally, some numerical examples are given to illustrate the theoretical results. (shrink)

This survey is the first to review the combination of computational trust and argumentation. The combination of the two approaches seems like a natural match, with the two areas tackling different aspects of reasoning in an uncertain, social environment. We discuss the different areas of research and describe the approaches taken so far, analysing both how they address the problems and the challenges that are unaddressed.

In this paper we address the problem of defining social roles in multi-agent systems. Social roles provide the basic structure of social institutions and organizations. We start from the properties attributed to roles both in the multi-agent systems and the Object Oriented community, and we use them in an ontological analysis of the notion of social role. We identify three main properties of social roles. First, they are definitionally dependent on the institution they belong to, i.e. (...) the definition of a role is given inside the definition of the institution. Second, they attribute powers to the agents playing them, like creating commitments for the institutions and the other roles. Third, they allow roles to play roles, in the same way as agents do. Using Input/Output logics, we propose a formalization of roles in multi-agent systems satisfying the three properties we identified. (shrink)

Although virtue ethics has repeatedly been proposed as a suitable framework for the development of artificial moral agents, it has been proven difficult to approach from a computational perspective. In this work, we present the first technical implementation of artificial virtuous agents in moral simulations. First, we review previous conceptual and technical work in artificial virtue ethics and describe a functionalistic path to AVAs based on dispositional virtues, bottom-up learning, and top-down eudaimonic reward. We then provide the details of a (...) technical implementation in a moral simulation based on a tragedy of the commons scenario. The experimental results show how the AVAs learn to tackle cooperation problems while exhibiting core features of their theoretical counterpart, including moral character, dispositional virtues, learning from experience, and the pursuit of eudaimonia. Ultimately, we argue that virtue ethics provides a compelling path toward morally excellent machines and that our work provides an important starting point for such endeavors. (shrink)

This theoretical paper takes an agency-theoretic approach to questions of corporate social responsibility (CSR). A comparison of various extant frameworks focusses on how CSR agency emerges in complex multi-agent and multi-sector stakeholder networks. The discussion considers the respective capabilities and relevance of these frameworks – culminating in an integrative CSR practice model. A short literature review of the evolution of CSR since the 1950’s provides the backdrop for understanding multi-agent cross-sectoral stakeholder coalitions as a strategic (...) determinant of today’s organizational behavior. The paper turns to Werhane’s coupling of moral imagination and systems thinking and forging stakeholder coalitions in problem contexts that were traditionally deemed intractable by for-profit organizations. However, it identifies the problem that the systems approach treats macro-agents (organizations, stakeholders) as given (“black-boxed”) and shies away from more radically re-imagining the possibilities of reassembling agency from the bottom up. Actor Network Theory (ANT) provides such a method, which strictly commits to treating organizational behavior as a product of technological, human and environmental micro-processes. ANT, however, is lacking a genuine moral deliberative stance in designing complex CSR coalitions. In an attempt to capitalize on the respective strengths of these frameworks (Systems thinking and ANT) the paper tends to a recent iterative series of “situational transactive” models that are rooted in the US pragmatist tradition and seek to capture intelligent planning processes in complex problematic contexts. The contribution proposes a new CSR practice model, which assigns specific roles to the theoretical contributions of ANT, system thinking and pragmatism in complex deliberation processes. This model can be industry-tested in a future study. (shrink)

Using a knowledge-based approach, we derive a protocol, MACOM1, for the sequence transmission problem from one agent to a group of agents. The protocol is correct for communication media where deletion and reordering errors may occur. Furthermore, it is shown that after k rounds the agents in the group attain depth k general knowledge about the members of the group and the values of the messages. Then, we adjust this algorithm for multi-agent communication for the process of (...) teamwork. MACOM1 solves the sequence transmission problem from one agent to a group of agents, but does not fully comply with the type of dialogue communication needed for teamwork. The number of messages being communicated per communication between the initiator and the other agents from the group can differ. Furthermore, the teamwork process can require the communication algorithm to handle changes of initiator. We show the adjustments that have to be made to MACOM1 to handle these properties of teamwork. For the new multi-agent communication algorithm, MACOM2, it is shown that the gaining of knowledge required for a successful teamwork process is still guaranteed. (shrink)

In this article, we compare two fixed-point constructions of common knowledge in sequential coordination problems. The first one corresponds to the standard maximal fixed-point construction of common knowledge in a possible worlds framework; the second construction provides an even larger fixed-point and involves iterated epistemic updates. We call the first fixed-point the maximal fixed-point, and the second the update fixed-point. Both fixed-points define a set of sequential actions that solve the coordination problem such that success is mutually guaranteed. The (...) main application intended is the study of signalling games as introduced by [15]. We introduce a non-probabilistic version of these games as multi-agent signalling games. We use them for modelling prototypical accommodation phenomena following [16]. We show especially that accommodation, which involves presupposition violation, is only licensed due to the existence of the super large update fixed-point, whereas the literal language use without presupposition violations can be characterized by the maximal fixed-point. (shrink)

In multi-armed bandit problems, information acquired from experimentation is valuable because it tells the agent whether to select a particular option again in the future. This article tests whether people undervalue this information because they are ambiguity averse, or have a distaste for uncertainty about the average quality of each alternative. It is shown that ambiguity averse agents have lower than optimal Gittins indexes, appearing to undervalue information from experimentation, but are willing to pay more than ambiguity (...) neutral agents to learn the true mean of the payoff distribution, appearing to overvalue objectively given information. This prediction is tested with a laboratory experiment that elicits a Gittins index and a willingness to pay on six two-armed bandits. Consistent with the predictions of ambiguity aversion, the Gittins indexes are significantly lower than optimal and willingnesses to pay are significantly higher than optimal. (shrink)

The objective of this work is to demonstrate how cooperative sharers and uncooperative free riders can be placed in different groups of an electronic society in a decentralised manner. We have simulated an agent-based open and decentralised P2P system which self-organises itself into different groups to avoid cooperative sharers being exploited by uncooperative free riders. This approach encourages sharers to move to better groups and restricts free riders into those groups of sharers without needing centralised control. Our approach is (...) suitable for current P2P systems that are open and distributed. Gossip is used as a social mechanism for information sharing which facilitates the formation of groups. Using multi-agent based simulations we demonstrate how the adaptive behaviour of agents lead to self-organisation. We have tested with varying the gossip level and checked its impact in the system’s behaviour. We have also investigated the impact of false gossip in this system where gossip is the medium for information sharing which leads to self-organisation. (shrink)

The paper introduces the problem of unawareness into multi-dimensional Principal–Agent theory. We introduce two key parameters to describe the problem, the extent and the effect of unawareness, show under what conditions it is optimal for the Principal to propose an incomplete or a complete contract, and characterize the incentive power of optimal linear contracts. If Agents differ in their unawareness, optimal incentive schemes can be distorted for both aware and unaware Agents, because, different from standard contract theory, the (...) single-crossing property fails to hold. In this case, even aware Agents can be subject to inefficiently high or low incentives. (shrink)

In modern technical societies computers interact with human beings in ways that can affect moral rights and obligations. This has given rise to the question whether computers can act as autonomous moral agents. The answer to this question depends on many explicit and implicit definitions that touch on different philosophical areas such as anthropology and metaphysics. The approach chosen in this paper centres on the concept of information. Information is a multi-facetted notion which is hard to define comprehensively. However, (...) the frequently used definition of information as data endowed with meaning can promote our understanding. It is argued that information in this sense is a necessary condition of cognitivist ethics. This is the basis for analysing computers and information processors regarding their status as possible moral agents. Computers have several characteristics that are desirable for moral agents. However, computers in their current form are unable to capture the meaning of information and therefore fail to reflect morality in anything but a most basic sense of the term. This shortcoming is discussed using the example of the Moral Turing Test. The paper ends with a consideration of which conditions computers would have to fulfil in order to be able to use information in such a way as to render them capable of acting morally and reflecting ethically. (shrink)

Counterfactual attitudes like imagining, dreaming, and wishing create a problem for the standard formal semantic theory of de re attitude ascriptions. I show how the problem can be avoided if we represent an agent's attitudinal possibilities using "multi-centered worlds", possible worlds with multiple distinguished individuals, each of which represents an individual with whom the agent is acquainted. I then present a compositional semantics for de re ascriptions according to which singular terms are "assignment-sensitive" expressions and attitude verbs (...) are "assignment shifters". (shrink)

In this paper I will discuss a certain philosophical and conceptual program -- that I have called philosophy of social action writ large -- and also show in detail how parts of the program have been, and is currently being carried out. In current philosophical research the philosophy of social action can be understood in a broad sense to encompass such central research topics as action occurring in a social context (this includes multi-agent action); shared we-attitudes (such as (...) we-intention, mutual belief) and other social attitudes expressing collective intentionality and needed for the explication and explanation of social action; social macro-notions, such as actions performed by social groups and properties of social groups such as their goals and beliefs; social practices, and institutions (see e.g. Tuomela, 1995, 2000a, 2001). The theory of social action understood analogously in a broad sense would then involve not only philosophical but all other relevant theorizing about social action. Thus, in this sense, such fields of Artificial Intelligence (AI) as Distributed AI (DAI) and the theory of Multi-Agent Systems (MAS) fall within the scope of the theory of social action. DAI studies the social side of computer systems and includes various well-known areas ranging from human-computer interaction, computer-supported cooperative work, organizational processing, and distributed problem solving to the simulation of social systems. (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)

There is a very striking difference between even the simplest ethnographically known human societies and those of the chimps and bonobos. Chimp and bonobo societies are closed societies: with the exception of adolescent females who disperse from their natal group and join a nearby group (never to return to their group of origin), a pan residential group is the whole social world of the agents who make it up. That is not true of forager bands, which have fluid memberships, and (...) regular associations with neighbouring bands. They are components of a larger social world. The open and fluid character of forager bands brings with it many advantages, so the stability of this more vertically complex form of social life is not difficult to explain, once it establishes. But how did it establish, if, as is likely, earlier hominin social worlds resemble those of our close pan relatives in the suspicion (even hostility) of one band to another? How did hominin social organisation transition from life in closed bands, each distrustful of its neighbours, to the much more open social lives of foragers? I will discuss and synthesise two approaches to this problem, one ecological, based on the work of Robert Layton and his colleagues, and another that is organised around an expansion of kin recognition, an idea primarily driven by Bernard Chapais. The paper closes by discussing potential archaeological signatures both of more open social worlds, and of the supposed causal drivers of such worlds. (shrink)

This article provides overview of the swarm intelligence and robotics fields, main characteristics of such systems provided, their advantages and disadvantages as well as differences from other multi-agent systems. Also, main fields of application for swarm systems with examples provided apart from short information on swarm optimizations. The problem of swarms’ control described and possible solutions for it such as algorithm replacement, parameters change, control through environment and leaders. Apart from that fields for possible future research noted.

The paper argues that much of the difficulty with making progress on the issue of the normativity of logic for thought, as discussed in the literature, stems from a misapprehension of what logic is normative for. The claim is that, rather than mono-agent mental processes, logic in fact comprises norms for quite specific situations of multi-agent dialogical interactions, in particular special forms of debates. This reconceptualization is inspired by historical developments in logic and mathematics, in particular the (...) pervasiveness of such dialogical conceptions in the early days of logic in ancient Greece. The multi-agent, dialogical perspective then allows for the formulation of compelling 'bridge principles’ between the relation of logical consequence and dialogical normative principles, something that is notoriously difficult to achieve in a mono-agent setting pertaining exclusively to thought and belief. The upshot is also that the truth-preserving rules of logic generally do not have a primary normative bearing on mono-agent mental processes, and in this sense the paper sides with Harman's critique of the idea that logic has a normative import for thought and belief. (shrink)

In order to design and implement electronic institutions that incorporate norms governing the behavior of the participants of those institutions, some crucial steps should be taken. The first problem is that human norms are (on purpose) specified on an abstract level. This ensures applicability of the norms over long periods of time in many different circumstances. However, for an electronic institution to function according to those norms, they should be concrete enough to be able to check them run time. A (...) second problem is that norms describe which behavior is desirable and permitted, but not how this is achieved in an institution. In the “real world" regulations often indicate procedures for implementing and enforcing the law. Likewise we should devise means to annotate the norms with practical aspects such as enforcement mechanisms, sanctions, etc. in order to get requirements for an institution that will enforce norms (by either constraining behavior within the norms or reacting to violation of the norms). The choice of which kind of mechanism is chosen is not a normative one, but usually based on criteria of efficiency and/or feasibility of the mechanism. In this paper we present our view on how to approach these problems and other related issues to be solved in order to develop e-institutions capable to operate in complex, highly regulated scenarios. (shrink)

In a multiagent and multi-cultural world, the fine-grained analysis of agents’ dynamic behaviour, i.e. of their activities, is essential. Dynamic activities are actions that are characterized by an agent who executes the action and by other participants of the action. Wh-questions on the participants of the actions pose a difficult particular challenge because the variability of the types of possible answers to such questions is huge. To deal with the problem, we propose the analysis and classification of Wh-questions (...) apt for agents’ communication in a multiagent system (MAS). Our proposal of such a system consists of agents who communicate with their fellow agents by messaging so that each autonomous agent, though resource-bounded, can make less or more rational decisions to meet its own and collective goals. In addition, by communicating with other fellow agents and their environment, agents can learn new concepts and enrich their ontology so that their behaviour is dynamic. We aim to make a general proposal of the system so that the ‘envelope’ of agents’ messages can be formalized in any MAS standard, be it The Foundation for Intelligent Physical Agents - Agent Communication Language (FIPA-ACL) or Knowledge Query and Manipulation Language (KQML). Yet, the content of messages is encoded in a formalized natural language. To this end, we apply Transparent Intensional Logic (TIL) with its procedural semantics which is particularly apt for a fine-grained analysis in which all the semantically salient features of natural language can be plausibly formalized. In this paper, we concentrate on analysing the content of query messages, particularly the content of those that encode Wh-questions and the answers to them. We also summarize TIL deduction system that makes it possible to answer such questions in an intelligent way. Linguists distinguish several subtypes of Wh-questions. Though the linguistic classification is helpful, it is not always suitable for agents’ communication and reasoning. We need the classification based on a logical analysis of Wh-questions so that the agents can infer possible answers to such questions rather than only looking for them by keywords. This paper aims to apply an appropriate classification of the logical types of Wh-questions and the analysis of such questions; we concentrate in particular on questions concerning the participants of activities. The application of these results to the analysis of processes and events based on verb valency frames is another novelty of the paper. (shrink)

Many collective decision making problems have a combinatorial structure: the agents involved must decide on multiple issues and their preferences over one issue may depend on the choices adopted for some of the others. Voting is an attractive method for making collective decisions, but conducting a multi-issue election is challenging. On the one hand, requiring agents to vote by expressing their preferences over all combinations of issues is computationally infeasible; on the other, decomposing the problem into several elections (...) on smaller sets of issues can lead to paradoxical outcomes. Any pragmatic method for running a multi-issue election will have to balance these two concerns. We identify and analyse the problem of generating an agenda for a given election, specifying which issues to vote on together in local elections and in which order to schedule those local elections. (shrink)

Infonorma is a multi-agent system that provides its users with recommendations of legal normative instruments they might be interested in. The Filter agent of Infonorma classifies normative instruments represented as Semantic Web documents into legal branches and performs content-based similarity analysis. This agent, as well as the entire Infonorma system, was modeled under the guidelines of MAAEM, a software development methodology for multi-agent application engineering. This article describes the Infonorma requirements specification, the architectural design (...) solution for those requirements, the detailed design of the Filter agent and the implementation model of Infonorma, according to the guidelines of the MAAEM methodology. (shrink)

AI research is being challenged with ensuring that autonomous agents learn to behave ethically, namely in alignment with moral values. Here, we propose a novel way of tackling the value alignment problem as a two-step process. The first step consists on formalising moral values and value aligned behaviour based on philosophical foundations. Our formalisation is compatible with the framework of (Multi-Objective) Reinforcement Learning, to ease the handling of an agent’s individual and ethical objectives. The second step consists in (...) designing an environment wherein an agent learns to behave ethically while pursuing its individual objective. We leverage on our theoretical results to introduce an algorithm that automates our two-step approach. In the cases where value-aligned behaviour is possible, our algorithm produces a learning environment for the agent wherein it will learn a value-aligned behaviour. (shrink)

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval.When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based (...) system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. (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 specification”, “behavior of models”, “simulator” and “endomorphic agents” can be partially translated in the terms linked to the “denotational hierarchy” (DH) and 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)

The paper presents a family of propositional epistemic logics such that languages of these logics are extended by quantification over modal operators or over agents of knowledge and extended by predicate symbols that take modal operators as arguments. Denote this family by \}\). There exist epistemic logics whose languages have the above mentioned properties :311–350, 1995; Lomuscio and Colombetti in Proceedings of ATAL 1996. Lecture Notes in Computer Science, vol 1193, pp 71–85, 1996). But these logics are obtained from first-order (...) modal logics, while a logic of \}\) can be regarded as a propositional multi-modal logic whose language includes quantifiers over modal operators and predicate symbols that take modal operators as arguments. Among the logics of \}\) there are logics with a syntactical distinction between two readings of epistemic sentences: de dicto and de re. We show the decidability of logics of \}\) with the help of the loosely guarded fragment of first-order logic. Namely, we generalize LGF to a higher-order decidable loosely guarded fragment. The latter fragment allows us to construct various decidable propositional epistemic logics with quantification over modal operators. The family of this logics coincides with \}\). There are decidable propositional logics such that these logics implicitly contain quantification over agents of knowledge, but languages of these logics are usual propositional epistemic languages without quantifiers and predicate symbols :345–378, 1993). Some logics of \}\) can be regarded as counterparts of logics defined in Grove and Halpern :345–378, 1993). We prove that the satisfiability problem for these logics of \}\) is Pspace-complete using their counterparts in Grove and Halpern :345–378, 1993). (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)

In [11] it is shown how propositional dynamic logic (PDL) can be interpreted as a logic of belief revision that extends the logic of communication and change (LCC) given in [7]. This new version of epistemic/doxastic PDL does not impose any constraints on the basic relations and because of this it does not suffer from the drawback of LCC that these constraints may get lost under updates that are admitted by the system. Here, we will impose one constraint, namely that (...) the agent’s plausibility relations are linked. Linkedness is a natural extension of local connectedness to the multi-agent case and it assures that we know the agent’s preferences between all relevant alternatives. Since the belief updates that are used in [11] may not preserve linkedness, we limit ourselves to a particular kind of belief change that does preserve it. Our framework has obvious connections to coalition logic [17] and social choice theory [19]. We show how we can use it to model consensus seeking in plenary Dutch meetings. In Dutch meetings, a belief update is done for all agents in the meeting if a majority beliefs the proposition that is under discussion. A special case of these meetings is judgement aggregation, and we apply our framework to the discursive dilemma in this field [15]. (shrink)

Many computational tools for the simulation and design of emergency evacuation and egress are now available. However, due to the scarcity of human and social behavioral data, these computational tools rely on assumptions that have been found inconsistent or unrealistic. This paper presents a multi-agent based framework for simulating human and social behavior during emergency evacuation. A prototype system has been developed, which is able to demonstrate some emergent behaviors, such as competitive, queuing, and herding behaviors. For illustration, (...) an example application of the system for safe egress design is provided. (shrink)

This paper addresses weighting and partitioning in complex reinforcement learning tasks, with the aim of facilitating learning. The paper presents some ideas regarding weighting of multiple agents and extends them into partitioning an input/state space into multiple regions with di erential weighting in these regions, to exploit di erential characteristics of regions and di erential characteristics of agents to reduce the learning complexity of agents (and their function approximators) and thus to facilitate the learning overall. It analyzes, in reinforcement learning (...) tasks, di erent ways of partitioning a task and using agents selectively based on partitioning. Based on the analysis, some heuristic methods are described and experimentally tested. We nd that some o -line heuristic methods performed the best, signi cantly better than single-agent models. (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.

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 knowledge economy, the process of knowledge sharing and creation for value co-creation frequently emerge in a multi-agent and multi-level system. It's important to consider the roles, functions, and possible interactive knowledge-based activities of key actors for ecological development. Makerspace as an initial stage of incubated platform plays the central and crucial roles of resource orchestrators and platform supporter. Less literature analyses the knowledge ecosystem embedded by makerspaces and considers the interactive process of civil society and (...) natural environment. This study constructs a multi-agent and multi-level knowledge ecosystem from macro, meso, and micro perspective based on Quintuple Helix theory and designs four evolutionary stages of knowledge orchestrating processes. This study finds that the symbiosis, co-evolution, interaction, and orchestration of multiple agents in the knowledge ecosystem should be merged with each other for value co-creation, which helps to take a systematic approach for policymakers, managers, and researchers. (shrink)

This paper presents a logic combining Dynamic Epistemic Logic, a framework for reasoning about multi-agent communication, with a new multi-agent version of Justification Logic, a framework for reasoning about evidence and justification. This novel combination incorporates a new kind of multi-agent evidence elimination that cleanly meshes with the multi-agent communications from Dynamic Epistemic Logic, resulting in a system for reasoning about multi-agent communication and evidence elimination for groups of interacting rational (...) agents. (shrink)

In this paper we forge a connection between dynamic epistemic logics of belief revision on one hand and studies of collective judgement and multi-agent preference change on the other. Belief revision in the spirit of dynamic epistemic logic uses updating with relational substitutions to change the beliefs of individual agents. Collective judgement in social choice theory studies the collective outcomes of individual belief changes. We start out from the logic of communication and change (LCC), which is basically epistemic (...) propositional dynamic logic (PDL) extended with update action modalities. We show how epistemic PDL can be made to handle belief operators. Our new version of epistemic/doxastic PDL does not impose any constraints on the basic relations. Because of this it does not suffer from the drawback of LCC that constraints on epistemic relations, such as transitivity and reflexivity, may get lost under updates that are admitted by the system. After introducing the base system without constraints, we study the effects of imposing a single constraint, namely the constraint that the agent’s preference relations are linked. Linkedness is a natural extension of local connectedness to the multi-agent case. It assures that if Alice prefers y to x and Bob prefers z to x, then both Alice and Bob can make up their minds when given a choice between y and z. Since general belief changes may not preserve linkedness, we propose a recipe for belief change that does preserve it. Finally, we show that the resulting framework can be used to model consensus seeking procedures. We focus on the case of plenary Dutch meetings. In Dutch meetings, a belief change (or rather: preference change) is performed for all agents in the meeting if a majority believes (or: is in favour of) the proposition that is under discussion. A special case of these meetings is judgement aggregation, and we apply our framework to the discursive dilemma in.. (shrink)