From the Publisher:
An agent is an entity with domain knowledge, goals and actions. Multi-agent systems are a set of agents which
interact in a common environment. Multi-agent systems deal with the construction of complex systems involving multiple agents and their coordination. A multi-agent system (MAS) is a distributed computing system with
autonomous interacting intelligent agents that coordinate their actions so as to achieve its goal(s) jointly or competitively.

Introduction to Multiagent Systems

Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaikos book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, and artificial intelligence. The second edition of Ontology Matching has been thoroughly revised and updated to reflect the most recent advances in this quickly developing area, which resulted in more than 150 pages of new content. In particular, the book includes a new chapter dedicated to the methodology for performing ontology matching. It also covers emerging topics, such as data interlinking, ontology partitioning and pruning, context-based matching, matcher tuning, alignment debugging, and user involvement in matching, to mention a few. More than 100 state-of-the-art matching systems and frameworks were reviewed. With Ontology Matching, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can be equally applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a systematic and detailed account of matching techniques and matching systems from theoretical, practical and application perspectives.

Ontology Matching

Theory of fuzzy integrals and its applications

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Automated Negotiation: Prospects, Methods and Challenges

Argumentation in artificial intelligence

Argumentation is a reasoning model based on the construction of arguments and counter-arguments (or defeaters) followed by the selection of the most acceptable of them. In this paper, we refine the argumentation framework proposed by Dung by taking into account preference relations between arguments in order to integrate two complementary points of view on the concept of acceptability: acceptability based on the existence of direct counter-arguments and acceptability based on the existence of defenders. An argument is thus acceptable if it is preferred to its direct defeaters or if it is defended against its defeaters. This also refines previous works by Prakken and Sartor, by associating with each argument a notion of strength, while these authors embed preferences in the definition of the defeat relation. We propose a revised proof theory in terms of AND/OR trees, verifying if a given argument is acceptable, which better reflects the dialectical form of argumentation.

A Reasoning Model Based on the Production of Acceptable Arguments

On the evaluation of argumentation formalisms

A number of authors have suggested the use of argumentation techniques as the basis for negotiation dialogues between agents. In this paper we augment this work by investigating the use of argumentation as the basis for a wider range of types of dialogue. The approach we take is based upon MacKenzie's dialogue game DC, and we show that a translation of this into our system of argumentation can support a subset of the types of dialogue identified by Walton and Krabbe (1995).

/pdf/modelling-dialogues-using-argumentation-6a6usgn7g8.pdf

Modelling dialogues using argumentation

Using arguments for making and explaining decisions

In the past few years there have been a number of proposals for mechanisms for negotiation between agents that make use of argumentation. These proposals have largely been vague on the subject of how the generation and interpretation of arguments fits into the process of negotiation. This paper addresses this gap, proposing a particular protocol which is suitable for negotiation, and illustrating its use on an example from the literature.

/pdf/arguments-dialogue-and-negotiation-4zpyg4eymc.pdf

Leila Amgoud

Papers

A Reasoning Model Based on the Production of Acceptable Arguments

On the evaluation of argumentation formalisms

Modelling dialogues using argumentation

Using arguments for making and explaining decisions

Arguments, dialogue, and negotiation