Congregating and market formation
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
IEEE Intelligent Systems
IEEE Intelligent Systems
Coordinated Reinforcement Learning
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Context-specific multiagent coordination and planning with factored MDPs
Eighteenth national conference on Artificial intelligence
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We take the position that for any goal achievable on the Semantic Web, there will be a "best" system of Web-dwelling software agents to realize that goal, and that such a system may be discovered effectively. The process of determining the "best" agent system may be overseen by a distinguished Manager Agent. But with realistic time and space constraints, and the dynamic nature of the Semantic Web, finding an approximating system may be acceptable. The approximation then may be adapted iteratively, to approach the ideal. We show that very practical researchers have looked at software agents and Semantic Web problems in a similar way, determining approximating sub-optimal systems and subsequently adapting them. Their applied research confirms that theory provides a good foundation for practice.