Specification and Verification of Multi-agent Systems presents a coherent treatment of the area of formal specification and verification of agent-based systems with a special focus on verification of multi-agent programs. This edited volume includes contributions from international leading researchers in the area, addressing logical formalisms and techniques, such as model checking, theorem proving, and axiomatisations for (semi) automatic verification of agent-based systems. Chapters include: • Using Theorem Proving to Verify Properties of Agent Programs • The Refinement of Multi-Agent Systems • Model Checking Agent Communication • Directions for Agent Model Checking • Model Checking Logics of Strategic Ability: Complexity • Correctness of Mult-Agent Programs: A Hybrid Approach • The Norm Implementation Problem in Normative Multi-Agent Systems • A Verification Logic for GOAL Agents • Using the Maude Term Rewriting Language for Agent Development with Formal Foundations • The Cognitive Agents Specification Language and Verification Environment • A Temporal Trace Language for Formal Modelling and Analysis of Agent Systemns • Assurance of Agent Systems: What Role Should Formal Verification Play? Specification and Verification of Multi-agent Systems is a comprehensive guide that makes a useful tool for researchers, practitioners and students, and serves as a reference work summarizing the state of the art in an accessible manner.

This book constitutes the refereed proceedings of the 5th International Central and Eastern European Conference on Multi-Agent Systems, CEEMAS 2007, held in Leipzig, Germany, September 25-27, 2007. The 29 revised full papers and 17 revised short papers presented together with an invited paper were carefully reviewed and selected from 84 submissions. The papers cover a wide range of areas.

Methodological Guidelines for Modeling and Developing MAS-Based Simulations The intersection of agents, modeling, simulation, and application domains has been the subject of active research for over two decades. Although agents and simulation have been used effectively in a variety of application domains, much of the supporting research remains scattered in the literature, too often leaving scientists to develop multi-agent system (MAS) models and simulations from scratch. Multi-Agent Systems: Simulation and Applications provides an overdue review of the wide ranging facets of MAS simulation, including methodological and application-oriented guidelines. This comprehensive resource reviews two decades of research in the intersection of MAS, simulation, and different application domains. It provides scientists and developers with disciplined engineering approaches to modeling and developing MAS-based simulations. After providing an overview of the field’s history and its basic principles, as well as cataloging the various simulation engines for MAS, the book devotes three sections to current and emerging approaches and applications. Simulation for MAS — explains simulation support for agent decision making, the use of simulation for the design of self-organizing systems, the role of software architecture in simulating MAS, and the use of simulation for studying learning and stigmergic interaction. MAS for Simulation — discusses an agent-based framework for symbiotic simulation, the use of country databases and expert systems for agent-based modeling of social systems, crowd-behavior modeling, agent-based modeling and simulation of adult stem cells, and agents for traffic simulation. Tools — presents a number of representative platforms and tools for MAS and simulation, including Jason, James II, SeSAm, and RoboCup Rescue. Complete with over 200 figures and formulas, this reference book provides the necessary overview of experiences with MAS simulation and the tools needed to exploit simulation in MAS for future research in a vast array of applications including home security, computational systems biology, and traffic management.

Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter* Handle qualitative and uncertain information* Improve computational tractability to solve your problems easily

This book constitutes the strictly refereed post-proceedings of the 6th International Workshop on Computational Logic for Multi-Agent Systems, CLIMA VI. The book presents 14 revised full technical papers, 4 contest papers, and 7 invited papers together with 1 invited article are organized in topical sections on foundational aspects of agency, agent programming, agent interaction and normative systems, the first CLIMA contest, and on the project report of the SOCS project.

Multi-agent systems are communities of problem-solving entities that can exhibit varying degrees of intelligence. They can perceive and react to their environment, they can have individual or joint goals, for which they can plan and execute actions. Work on such systems integrates many technologies and concepts in - ti?cial intelligence and other areas of computing as well as other disciplines. The agent paradigm has become widely popular and widely used in recent years, due to its applicability to a large range of domains, from search engines to edu- tional aids to electronic commerce and trade, e-procurement, recommendation systems, simulation and routing, and ambient intelligence, to cite only some. Computational logic provides a well-de?ned, general, and rigorous framework for studying syntax, semantics, and procedures for various capabilities and fu- tionalities of individual agents, as well as interaction amongst agents in multi-agent systems. It also provides a well-de?ned and rigorous framework for implemen- tions, environments, tools, and standards, and for linking together speci?cation and veri?cation of properties of individual agents and multi-agent systems. The CLIMA workshop series was founded to provide a forum for discussing, presenting, and promoting computational logic-based approaches in the design, development, analysis, and application of multi-agent systems.

This book constitutes the proceedings of the 14th International Workshop on Computational Logic in Multi-Agent Systems, CLIMA XIV, held in Corunna, Spain, in September 2013. The 23 regular papers were carefully reviewed and selected from 44 submissions and presented with four invited talks. The purpose of the CLIMA workshops is to provide a forum for discussing techniques, based on computational logic, for representing, programming and reasoning about agents and multi-agent systems in a formal way. This edition will feature two special sessions: Argumentation Technologies and Norms and Normative Multi-Agent Systems.