Successful multi-agent systems development is guaranteed only if we can bridge the gap from analysis and design to effective implementation. This contribution has been fragmented, without any clear way of “putting it all together”, rendering it inaccessible to students and young researchers, non-experts, and practitioners. The main focus of the research community has been on the development of concepts (concerning both mental and social attitudes), architectures, techniques, and general approaches to the analysis and specification of multi-agent systems.
Multi-Agent Systems are a promising technology to develop the next generation open distributed complex software systems.
A bibliography and index complete this comprehensive work. Each chapter also contains numerous student exercises (with solutions provided in an appendix) to reinforce concepts and challenge the learner. End-of-chapter bibliographic and historical comments provide background and point to other works of interest and research. The final three chapters discuss the representation of knowledge about states and actions, planning, and intelligent system architecture. This section also develops the process of writing predicate calculus sentences to the metalevel-to permit sentences about sentences and about reasoning processes. The third section introduces modal operators that facilitate representing and reasoning about knowledge. The next several chapters discuss nonmonotonic reasoning, induction, and reasoning under uncertainty, broadening the logical approach to deal with the inadequacies of strict logical deduction. This section also provides a simple but powerful inference procedure, resolution, and shows how it can be used in a reasoning system. The first section of the book introduces the logicist approach to AI-discussing the representation of declarative knowledge and featuring an introduction to the process of conceptualization, the syntax and semantics of predicate calculus, and the basics of other declarative representations such as frames and semantic nets. Intended both as a text for advanced undergraduates and graduate students, and as a key reference work for AI researchers and developers, Logical Foundations of Artificial Intelligence is a lucid, rigorous, and comprehensive account of the fundamentals of artificial intelligence from the standpoint of logic.