Multi-Agent Coordination and Cooperation in a Distributed Dynamic Environment with Limited Resources: Simulated Air Wars
Abstract
Coordination and cooperation are two major issues of concern in Distributed Artificial Intelligence (DAI) systems. How can a group of geographically distributed agents properly allocate a set of tasks among themselves? Also, in an environment of limited resources, how can agents resolve resource conflicts so as to effectively accomplish tasks? This research has examined these two problems and has implemented techniques to promote multi- agent coordination and cooperation. A method of negotiation allows agents to bid for tasks based upon the agents' capabilities. Furthermore, the use of a threshold value ensures that only the best agents for a task become task commanders, as well as allowing some tasks to be re-negotiated as agents improve their bids. To resolve resource conflicts, a technique known as Hierarchical Iterative Conflict Resolution has been used. This technique allows conflicts to be resolved in an iterative manner, based upon a hierarchy of task priorities. Agents with higher priority tasks have preference for borrowing resources from agents with lower priority tasks. This ensures that higher priority tasks will be solved before those of lower priority.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 1993
- Accession Number
- ADA275313
Entities
People
- Gregory D. Elder
Organizations
- Air Force Institute of Technology