THE DISTRIBUTED ARTIFICIAL INTELLIGENCE MELTING POT

Artiicial Intelligence (AI) has emphasized building \stand-alone systems" that can solve problems with minimal help from other systems (computer or human). These systems have traditionally been brittle, in the sense that they fail miserably when presented with problems even slightly outside of their limited range of expertise. The predominant AI answer to brittleness is to inject more knowledge into a system, including commonsense knowledge, to enlarge the system's range of capabilities. While in the short term such a strategy can overcome particular system limitations, it is in fact a very shortsighted strategy. A more powerful, extensible strategy for overcoming the inherent bounds of intelligence present i n a n y nite AI (or natural) system 64, 83, 84] is to put the system in a society o f systems, so that it can draw on a diverse collection of expertise and capabilities in the same way that people overcome the limitations of individuals by banding together into societies that are designed to accomplish what individuals cannot. The ability to exibly team up and coordinate group activities toward individual and collective goals is a hallmark of intelligence. Research in Distributed Artiicial Intelligence (DAI) concentrates on understanding the knowledge and reasoning techniques needed for intelligent coordination, and on embodying and evaluating this understanding in computer systems. In 1981, the Honorary Guest Editor for this special issue, Professor B. Chandrasekaran, guest edited a special issue of IEEE Transactions on Systems, Man, and Cybernetics that played a critical role in deening the eld of DAI. That special issue collected together articles that reeected the seminal ideas in the eld and asked many of the questions that have d r i v en DAI research since. Now, about ten years later, many of those questions have been answered, only to be replaced by new questions. A number of the contributing authors to the 1981 special issue remain active in the eld today, of whom three, Mark Fox, Carl Hewitt, and Victor Lesser, have co-authored papers in this special issue. They have been joined by a new and growing crop of researchers who, for the most part, have s t u m bled onto DAI from various directions, ranging from distributed computing systems to discourse analysis, from formalisms for representing nested beliefs in agents to cognitive studies of human performance in organizations, from solving inherently distributed problems in applications such as communication network managment to analyzing …