Coherent cooperation among communicating problem solvers
IEEE Transactions on Computers
Case-based planning: viewing planning as a memory task
Case-based planning: viewing planning as a memory task
Multiagent compromise via negotiation
Distributed Artificial Intelligence (Vol. 2)
The evolution of strategies for multiagent environments
Adaptive Behavior
Learning to coordinate without sharing information
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Distributed snapshots: determining global states of distributed systems
ACM Transactions on Computer Systems (TOCS)
IPUS: an architecture for the integrated processing and understanding of signals
Artificial Intelligence
Learning organizational roles for negotiated search in a multiagent system
International Journal of Human-Computer Studies - Evolution and learning in multiagent systems
Reflections on the Nature of Multi-Agent Coordination and Its Implications for an Agent Architecture
Autonomous Agents and Multi-Agent Systems
Explanation-Based Generalization: A Unifying View
Machine Learning
On-Line Learning of Coordination Plans
On-Line Learning of Coordination Plans
Evolution of the GPGP Domain-Independent Coordination Framework
Evolution of the GPGP Domain-Independent Coordination Framework
Proceedings of the third annual conference on Autonomous Agents
Learning quantitative knowledge for multiagent coordination
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Planning and learning together
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Hierarchical multi-agent reinforcement learning
Proceedings of the fifth international conference on Autonomous agents
Learning to select a coordination mechanism
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Recent Advances in Hierarchical Reinforcement Learning
Discrete Event Dynamic Systems
Reflections on the Nature of Multi-Agent Coordination and Its Implications for an Agent Architecture
Autonomous Agents and Multi-Agent Systems
Learning Situation-Specific Coordination in Cooperative Multi-agent Systems
Autonomous Agents and Multi-Agent Systems
An Adaptive Agent Society for Environmental Scanning through the Internet
PRIMA 2001 Proceedings of the 4th Pacific Rim International Workshop on Multi-Agents, Intelligent Agents: Specification, Modeling, and Applications
An Architectural Framework for Integrated Multiagent Planning, Reacting, and Learning
ATAL '00 Proceedings of the 7th International Workshop on Intelligent Agents VII. Agent Theories Architectures and Languages
Spatiotemporal Abstraction of Stochastic Sequential Processes
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
Distributed agents for cost-effective monitoring of critical success factors
Decision Support Systems
Learning implicit resource relationships from past plans in multi-agent systems
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Recent Advances in Hierarchical Reinforcement Learning
Discrete Event Dynamic Systems
Autonomous Agents that Learn to Better Coordinate
Autonomous Agents and Multi-Agent Systems
Evolution of the GPGP/TÆMS Domain-Independent Coordination Framework
Autonomous Agents and Multi-Agent Systems
Learning when and how to coordinate
Web Intelligence and Agent Systems
Coordination in multiagent reinforcement learning systems by virtual reinforcement signals
International Journal of Knowledge-based and Intelligent Engineering Systems
Robust agent teams via socially-attentive monitoring
Journal of Artificial Intelligence Research
Learning procedural knowledge to better coordinate
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
| Hi-index | 0.00 |
Coordination is an essential technique in cooperative, distributed multiagent systems. However, sophisticated coordination strategies are not always cost-effective in all problem-solving situations.This paper presents a learning method to identify what information will improvecoordination in specific problem-solving situations. Learning isaccomplished by recording and analyzing traces of inferences after problemsolving. The analysis identifies situations where inappropriatecoordination strategies caused redundant activities, or the lack of timelyexecution of important activities, thus degrading system performance. Toremedy this problem, situation-specific control rules are created whichacquire additional nonlocal information about activities in the agentnetworks and then select another plan or another schedulingstrategy. Examples from a real distributed problem-solving applicationinvolving diagnosis of a local area network are described.