Agent Theories, Architectures, and Languages: A Survey <s> Distributed AI <s> MINDS (Multiple Intelligent Node Document Servers) is a distributed system of knowledge-based query engines for efficiently retrieving multimedia documents in an office environment of distributed workstations. By learning document distribution patterns, as well as user interests and preferences during system usage, it customizes document retrievals for each user. A two-layer learning system has been implemented for MINDS. The knowledge base used by the query engine is learned at the lower level with the help of heuristics for assigning credit and recommending adjustments; these heuristics are incrementally refined at the upper level. <s> BIB001 </s> Agent Theories, Architectures, and Languages: A Survey <s> Distributed AI <s> Most artificial intelligence research investigates intelligent behavior for a single agent--solving problems heuristically, understanding natural language, and so on. Distributed Artificial Intelligence (DAI) is concerned with coordinated intelligent behavior: intelligent agents coordinating their knowledge, skills, and plans to act or solve problems, working toward a single goal, or toward separate, individual goals that interact. DAI provides intellectual insights about organization, interaction, and problem solving among intelligent agents. This comprehensive collection of articles shows the breadth and depth of DAI research. The selected information is relevant to emerging DAI technologies as well as to practical problems in artificial intelligence, distributed computing systems, and human-computer interaction. ::: ::: "Readings in Distributed Artificial Intelligence" proposes a framework for understanding the problems and possibilities of DAI. It divides the study into three realms: the natural systems approach (emulating strategies and representations people use to coordinate their activities), the engineering/science perspective (building automated, coordinated problem solvers for specific applications), and a third, hybrid approach that is useful in analyzing and developing mixed collections of machines and human agents working together. ::: ::: The editors introduce the volume with an important survey of the motivations, research, and results of work in DAI. This historical and conceptual overview combines with chapter introductions to guide the reader through this fascinating field. A unique and extensive bibliography is also provided. <s> BIB002 </s> Agent Theories, Architectures, and Languages: A Survey <s> Distributed AI <s> The problem definition and the functional architecture the DAI functionality of the architecture the communications functionality of the architecture the information modelling within the architecture the HCI requirements and components for the architecture an implementation using blackboards the application demonstrators. <s> BIB003
As we observed in section 1, there has been a marked flowering of interest in agent technology since the mid-1980s. This interest is in part due to the renewed interest in Distributed AI. Although DAI encompasses most of the issues we have discussed in this paper, it should be stressed that the classical emphasis in DAI has been on macro phenomona (the social level), rather than the micro phenomena (the agent level) that we have been concerned with in this paper. DAI thus looks at such issues as how a group of agents can be made to cooperate in order to efficiently solve problems, and how the activities of such a group can be efficiently coordinated. DAI researchers have applied agent technology in a variety of areas. Example applications include power systems management BIB003 , air traffic control  , and intelligent document retrieval BIB001 . The classic reference to DAI is BIB002 .