10,303 research outputs found

    OperA/ALIVE/OperettA

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    Comprehensive models for organizations must, on the one hand, be able to specify global goals and requirements but, on the other hand, cannot assume that particular actors will always act according to the needs and expectations of the system design. Concepts as organizational rules (Zambonelli 2002), norms and institutions (Dignum and Dignum 2001; Esteva et al. 2002), and social structures (Parunak and Odell 2002) arise from the idea that the effective engineering of organizations needs high-level, actor-independent concepts and abstractions that explicitly define the organization in which agents live (Zambonelli 2002).Peer ReviewedPostprint (author's final draft

    A commentary on standardization in the Semantic Web, Common Logic and MultiAgent Systems

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    Given the ubiquity of the Web, the Semantic Web (SW) offers MultiAgent Systems (MAS) a most wide-ranging platform by which they could intercommunicate. It can be argued however that MAS require levels of logic that the current Semantic Web has yet to provide. As ISO Common Logic (CL) ISO/IEC IS 24707:2007 provides a firstorder logic capability for MAS in an interoperable way, it seems natural to investigate how CL may itself integrate with the SW thus providing a more expressive means by which MAS can interoperate effectively across the SW. A commentary is accordingly presented on how this may be achieved. Whilst it notes that certain limitations remain to be addressed, the commentary proposes that standardising the SW with CL provides the vehicle by which MAS can achieve their potential.</p

    Geometric Aspects of Multiagent Systems

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    Recent advances in Multiagent Systems (MAS) and Epistemic Logic within Distributed Systems Theory, have used various combinatorial structures that model both the geometry of the systems and the Kripke model structure of models for the logic. Examining one of the simpler versions of these models, interpreted systems, and the related Kripke semantics of the logic S5nS5_n (an epistemic logic with nn-agents), the similarities with the geometric / homotopy theoretic structure of groupoid atlases is striking. These latter objects arise in problems within algebraic K-theory, an area of algebra linked to the study of decomposition and normal form theorems in linear algebra. They have a natural well structured notion of path and constructions of path objects, etc., that yield a rich homotopy theory.Comment: 14 pages, 1 eps figure, prepared for GETCO200

    Logic-Based Specification Languages for Intelligent Software Agents

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    The research field of Agent-Oriented Software Engineering (AOSE) aims to find abstractions, languages, methodologies and toolkits for modeling, verifying, validating and prototyping complex applications conceptualized as Multiagent Systems (MASs). A very lively research sub-field studies how formal methods can be used for AOSE. This paper presents a detailed survey of six logic-based executable agent specification languages that have been chosen for their potential to be integrated in our ARPEGGIO project, an open framework for specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each executable language, the logic foundations are described and an example of use is shown. A comparison of the six languages and a survey of similar approaches complete the paper, together with considerations of the advantages of using logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal "Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe Editor-in-Chie

    Extend Commitment Protocols with Temporal Regulations: Why and How

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    The proposal of Elisa Marengo's thesis is to extend commitment protocols to explicitly account for temporal regulations. This extension will satisfy two needs: (1) it will allow representing, in a flexible and modular way, temporal regulations with a normative force, posed on the interaction, so as to represent conventions, laws and suchlike; (2) it will allow committing to complex conditions, which describe not only what will be achieved but to some extent also how. These two aspects will be deeply investigated in the proposal of a unified framework, which is part of the ongoing work and will be included in the thesis.Comment: Proceedings of the Doctoral Consortium and Poster Session of the 5th International Symposium on Rules (RuleML 2011@IJCAI), pages 1-8 (arXiv:1107.1686

    Specification and Verification of Commitment-Regulated Data-Aware Multiagent Systems

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    In this paper we investigate multi agent systems whose agent interaction is based on social commitments that evolve over time, in presence of (possibly incomplete) data. In particular, we are interested in modeling and verifying how data maintained by the agents impact on the dynamics of such systems, and on the evolution of their commitments. This requires to lift the commitment-related conditions studied in the literature, which are typically based on propositional logics, to a first-order setting. To this purpose, we propose a rich framework for modeling data-aware commitment-based multiagent systems. In this framework, we study verification of rich temporal properties, establishing its decidability under the condition of “state-boundedness”, i.e., data items come from an infinite domain but, at every time point, each agent can store only a bounded number of them

    Human-Agent Decision-making: Combining Theory and Practice

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    Extensive work has been conducted both in game theory and logic to model strategic interaction. An important question is whether we can use these theories to design agents for interacting with people? On the one hand, they provide a formal design specification for agent strategies. On the other hand, people do not necessarily adhere to playing in accordance with these strategies, and their behavior is affected by a multitude of social and psychological factors. In this paper we will consider the question of whether strategies implied by theories of strategic behavior can be used by automated agents that interact proficiently with people. We will focus on automated agents that we built that need to interact with people in two negotiation settings: bargaining and deliberation. For bargaining we will study game-theory based equilibrium agents and for argumentation we will discuss logic-based argumentation theory. We will also consider security games and persuasion games and will discuss the benefits of using equilibrium based agents.Comment: In Proceedings TARK 2015, arXiv:1606.0729

    A Study of AI Population Dynamics with Million-agent Reinforcement Learning

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    We conduct an empirical study on discovering the ordered collective dynamics obtained by a population of intelligence agents, driven by million-agent reinforcement learning. Our intention is to put intelligent agents into a simulated natural context and verify if the principles developed in the real world could also be used in understanding an artificially-created intelligent population. To achieve this, we simulate a large-scale predator-prey world, where the laws of the world are designed by only the findings or logical equivalence that have been discovered in nature. We endow the agents with the intelligence based on deep reinforcement learning (DRL). In order to scale the population size up to millions agents, a large-scale DRL training platform with redesigned experience buffer is proposed. Our results show that the population dynamics of AI agents, driven only by each agent's individual self-interest, reveals an ordered pattern that is similar to the Lotka-Volterra model studied in population biology. We further discover the emergent behaviors of collective adaptations in studying how the agents' grouping behaviors will change with the environmental resources. Both of the two findings could be explained by the self-organization theory in nature.Comment: Full version of the paper presented at AAMAS 2018 (International Conference on Autonomous Agents and Multiagent Systems
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