Multiagent Systems - A Theoretical Framework for Intentions, Know-How, and Communications

the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag. Violations are liable for prosecution under the German Copyright Law. Foreword Distributed artificial intelligence (DAI) is a melding of artificial intelligence with distributed computing. From artificial intelligence comes the theory and technology for constructing or analyzing an intelligent system. But where artificial intelligence uses psychology as a source of ideas, inspiration, and metaphor, DAI uses sociology, economics, and management science for inspiration. Where the focus of artificial intelligence is on the individual, the focus of DAI is on the group. Distributed computing provides the computational substrate on which this group focus can occur. However, DAI is more than just the design of intelligent systems. It also provides insights and understanding about interactions among humans, as they organize themselves into various groups, committees, societies, and economies in order to improve their lives. For example, economists have been studying multiple agents for more than two hundred years, ever since Adam Smith in the eighteenth century, with the goal of being able to understand and predict economies. Economics provides ways to characterize masses of agents, and these are useful for DAI. But in return, DAI provides a means to construct artificial economies that can test economists' theories before, rather than after, they are applied. Distributed artificial intelligence has become a growing and maturing subfield of computer science. Since the first organized gathering of researchers in DAI at an MIT workshop in 1979, there have been twelve DAI Workshops in the U.S.A., five MAAMAW Workshops in Europe, two CKBS Workshops in England, two MACC Workshops in Japan, and numerous meetings associated with other conferences. A substantial body of results, in the form of theories and working systems, has already been produced. As I write this foreword in late 1993, there are plans underway for five DAI-related colloquia in the next six months and an International Conference the following year. This level of interest around the globe is significant. It is indicative of the importance that DAI has attained in computer science, and of the quality and quantity of research that …