Intelligent Adaptive Information Agents
Journal of Intelligent Information Systems - Special issue: adaptive intelligent agents
Partitioned multiagent systems in information oriented domains
Proceedings of the third annual conference on Autonomous Agents
Coordinating Mutually Exclusive Resources using GPGP
Autonomous Agents and Multi-Agent Systems
L-VIBRA: Learning the VIBRA Architecture
IBERAMIA-SBIA '00 Proceedings of the International Joint Conference, 7th Ibero-American Conference on AI: Advances in Artificial Intelligence
Evolving Real-Time Local Agent Control for Large-Scale Multi-agent Systems
ATAL '01 Revised Papers from the 8th International Workshop on Intelligent Agents VIII
Agents, self-interest and electronic markets
The Knowledge Engineering Review
Agent oriented software engineering with web applications
International Journal of Web Engineering and Technology
Organization oriented programming: from closed to open organizations
ESAW'06 Proceedings of the 7th international conference on Engineering societies in the agents world VII
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Many researchers have shown that there is no single best organization or coordination mechanism for all environments. This paper discusses the design and implementation of an extendable family of coordination mechanisms, called Generalized Partial Global Planning (GPGP). The set of coordination mechanisms described here assists in scheduling activities for teams of cooperative computational agents. The GPGP approach has several unique features. First, it is not tied to a single domain. Each mechanism is defined as a response to certain features in the current task environment. We show that different combinations of mechanisms are appropriate for different task environments. Secondly, the approach works in conjunction with an agent''s existing local planner/scheduler. Finally, the initial set of five mechanisms presented here generalizes and extends the Partial Global Planning (PGP) algorithm. In comparison to PGP, GPGP schedules tasks with deadlines, it allows agent heterogeneity, it exchanges less global information, and it communicates at multiple levels of abstraction. We analyze the performance of several GPGP algorithm family members and one centralized upper bound reference algorithm, using data from simulations of multiple agent teams working in abstract task environments. We show how to decide if adding a new mechanism is useful, and suggest a way to prune the search for an appropriate combination of mechanisms in an environment.