Socially situated planning provides one mechanism for improving the social awareness ofagents. Obviously this work isin the preliminary stages and many of the limitation and the relationship to other work could not be addressed in such a short chapter. The chief limitation, of course, is the strong commitment to de?ning social reasoning solely atthe meta-level, which restricts the subtlety of social behavior. Nonetheless, our experience in some real-world military simulation applications suggest that the approach, even in its preliminary state, is adequate to model some social interactions, and certainly extends the sta- of-the art found in traditional training simulation systems. Acknowledgments This research was funded by the Army Research Institute under contract TAPC-ARI-BR References [1] J. Gratch. Emile: Marshalling passions in training and education. In Proceedings of the Fourth International Conference on Autonomous Agents, pages 325–332, New York, 2000. ACM Press. [2] J. Gratch and R. Hill. Continous planning and collaboration for command and control in joint synthetic battlespaces. In Proceedings of the 8th Conference on Computer Generated Forces and Behavioral Representation, Orlando, FL, 1999. [3] B. Grosz and S. Kraus. Collaborative plans for complex group action. Arti?cial Intelli gence, 86(2):269–357, 1996. [4] A. Ortony, G. L. Clore, and A. Collins. The Cognitive Structure of Emotions. Cambridge University Press, 1988. [5] R.W.PewandA.S.Mavor,editors. Modeling Human and Organizational Behavior. National Academy Press, Washington D.C., 1998.

Social Order in Multiagent Systems provides an overview of current approaches, problems, and considerations related to the study of norms and institutions in the context of multiagent systems. The contributions in this volume share the assumption that norms and other social institutions are of vital importance for the development of multiagent systems and agent-mediated interaction. Both formal and computational models of norms and normative systems are presented, including formal analysis of normative concepts and foundational models of norms; agent and systems architectures for implementing norms; and implemented systems. Social Order in Multiagent Systems is an excellent reference for researchers in artificial intelligence and computer science, and can be used as text for advanced level courses in multiagent systems.

Conceptual Modelling of Multi-Agent Systems proposes the methodology and engineering environment CoMoMAS for the development of multi-agent systems. CoMoMAS is among the most elaborated and most often cited multi-agent development approaches available in the field. Its originality is to address the issue of the development of multi-agent systems (MAS) from a knowledge engineering perspective, which means that agents are seen as interacting entities having different kinds of knowledge, which is to be identified during development. Knowledge has played an important role for MAS development in the past, but CoMoMAS makes a step further in proposing a complete set of conceptual models and a solid methodology to guide the overall development process of a MAS-from design to validation. Conceptual Modelling of Multi-Agent Systems is an excellent reference for both researchers and practitioners in the broad area of distributed systems development. This book is of particular value from the point of view of computer science, including knowledge engineering, artificial intelligence, agent and multi-agent technology, and software engineering.

Conflicts between agents acting in a multi-agent environment arise for different reasons, involve different concepts, and are dealt with in different ways, depending on the kind of agents and on the domain where they are considered. Agents may have conflicting beliefs, conflicting goals, or may have to share limited resources. Consequently, conflicts may be expressed as mere differences, or as contradictions, or even as social conflicts. They may be avoided, solved, kept, or even created deliberately. Conflicting Agents studies conflicts in the context of multi-agent systems, i.e. artificial societies modeled on the basis of autonomous, interacting agents. This book addresses questions about types of conflicts, conflict definitions and the use of conflicts as trigger functions for activities in multi-agent systems. The book is also dedicated to questions of conflict management, resolution and avoidance, i.e. the question of how agents cope with conflicts and conflicting situations.

An interdisciplinary overview of current research on imitation in animals and artifacts.

For the first time, a comprehensive collection of the latest developments in scripting and representation languages for life-like characters. The text introduces toolkits for authoring animated characters which further supports the practicality and ease of use of this new interface technology. As life-like characters is a vibrant research area, various applications have been designed and implemented. The text covers the most successful and promising applications, ranging from product presentation and student training to knowledge integration and interactive gaming. It also discusses the key challenges in the area and provides design guidelines for employing life-like characters.

Mark d'Inverno and Michael Luck present a formal approach to dealing with agents and agent systems in this second edition of Understanding Agent Systems. The Z specification language is used to establish an accessible and unified formal account of agent systems and inter-agent relationships. In particular, the framework provides precise and unambiguous meanings for common concepts and terms for agent systems, allows for the description of alternative agent models and architectures, and serves as a foundation for subsequent development of increasingly refined agent concepts. The practicability of this approach is verified by applying the formal framework to three detailed case studies. The book will appeal equally to researchers, students, and professionals in industry.