Distributed Artificial Intelligence
Distributed Artificial Intelligence
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Information Sciences: an International Journal - Special issue on information sciences—past, present, and future
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Belief Revision
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Rational Communication in Multi-Agent Environments
Autonomous Agents and Multi-Agent Systems
Trends in Cooperative Distributed Problem Solving
IEEE Transactions on Knowledge and Data Engineering
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IEEE Expert: Intelligent Systems and Their Applications
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Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
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RoboCup Rescue: A Grand Challenge for Multi-Agent Systems
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
On the Communication Complexity of Multilateral Trading: Extended Report
Autonomous Agents and Multi-Agent Systems
Multiagent resource allocation
The Knowledge Engineering Review
Hybrid negotiation for resource coordination in multiagent systems
Web Intelligence and Agent Systems
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
A Study of an Approach to the Collective Iterative Task Allocation Problem
IAT '07 Proceedings of the 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Journal of Artificial Intelligence Research
Methods for task allocation via agent coalition formation
Artificial Intelligence
Agent-based intelligent collaborative care management
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Designing intelligent healthcare operations
CARE@AI'09/CARE@IAT'10 Proceedings of the CARE@AI 2009 and CARE@IAT 2010 international conference on Collaborative agents - research and development
Sequential multi-agent exploration for a common goal
Web Intelligence and Agent Systems
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A major challenge in the field of Multi-Agent Systems is to enable autonomous agents to allocate tasks efficiently. This paper extends previous work on an approach to the collective iterative allocation problem where a group of agents endeavours to find the best allocations possible through refinements of these allocations over time. For each iteration, each agent proposes an allocation based on its model of the problem domain, then one of the proposed allocations is selected and executed which enables us to assess if subsequent allocations should be refined. We offer an efficient algorithm capturing this process, and then report on theoretical and empirical results that analyse the role of three conditions in the performance of the algorithm: accuracy of agents' estimations of the performance of a task, the degree of optimism, and the type of group decision policy that determines which allocation is selected after each proposal phase.