Agents that reduce work and information overload
Communications of the ACM
Negotiation and cooperation in multi-agent environments
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Online learning about other agents in a dynamic multiagent system
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
SNMP: A Guide to Network Management
SNMP: A Guide to Network Management
The Communication of Inductive Inferences
ECAI '96 Selected papers from the Workshop on Distributed Artificial Intelligence Meets Machine Learning, Learning in Multi-Agent Environments
Semantics for an Agent Communication Language
ATAL '97 Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages
Determining Successful Negotiation Strategies: An Evolutionary Approach
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Distributed management by delegation
ICDCS '95 Proceedings of the 15th International Conference on Distributed Computing Systems
Schemes for scheduling control messages by hierarchical protocols
Computer Communications
Adaptive resource negotiation based control for real time applications
Computer Communications
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This paper presents how to make different agents cooperate to accomplish complex tasks and coordinate their objects, planning, knowledge and action, etc in dynamic and open multi-agent system. Using a hierarchical architecture, we implement a multi-agent prototype system-NHMAS in distributed network system environment. After briefly describing the framework of different agents and their functions, the paper discusses coordination mechanism of NHMAS in detail. We explore a heuristic strategy in task allocation. An advantage of this task allocation strategy is that it does not put extra loads on the system at critical times. For the need of coordinating different agent actions, we add partial order constraints between actions that have probability of conflicts and introduce our planning algorithm, conflict resolution and communication language. At last, we give a briefly performance analysis on Aglet workbench for NHMAS.