Statistical tools for simulation practitioners
Statistical tools for simulation practitioners
Coherent cooperation among communicating problem solvers
IEEE Transactions on Computers
Intention is choice with commitment
Artificial Intelligence
Information and Organizations
Quantitative Modeling of Complex Computational Task Environments
Quantitative Modeling of Complex Computational Task Environments
Coordinating Intelligent Agents
Selected papers from the UKMAS Workshop on Foundations and Applications of Multi-Agent Systems
A one-shot dynamic coordination algorithm for distributed sensor networks
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Quantitative modeling of complex computational task environments
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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This paper presents an analysis of static and dynamic organizational structures for naturally distributed, homogeneous, cooperative problem solving environments, exemplified by distributed sensor networks. We first show how the performance of any static organization can be statistically described, and then show under what conditions dynamic organizations do better and worse than static ones. Finally, we show how the variance in the agents' performance leads to uncertainty about whether a dynamic organization will perform better than a static one given only agent a priori expectations. In these cases, we show when meta-level communication about the actual state of problem solving will be useful to agents in constructing a dynamic organizational structure that outperforms a static one. Viewed in its entirety, this paper also presents a methodology for answering questions about the design of distributed problem solving systems by analysis and simulation of the characteristics of a complex environment rather than by relying on single-instance examples.