Multiagent Negotiation under Time Constraints

Research in distributed artificial intelligence (DAI) is concerned with how automated agents can be designed to interact effectively. Negotiation is proposed as a means for agents to communicate and compromise to reach mutually beneficial agreements. The paper examines the problems of resource allocation and task distribution among autonomous agents which can benefit from sharing a common resource or distributing a set of common tasks. We propose a strategic model of negotiation that takes the passage of time during the negotiation process itself into account. A distributed negotiation mechanism is introduced that is simple, efficient, stable, and flexible in various situations. The model considers situations characterized by complete as well as incomplete information, and ones in which some agents lose over time while others gain over time. Using this negotiation mechanism autonomous agents have simple and stable negotiation strategies that result in efficient agreements without delays even when there are dynamic changes in the environment.