Abstract
In previous work a negotiation protocol was developed and some negotiation strategies that are in equilibrium were presented. That negotiation process can be used only when the “negotiation set” (NS) is not empty. Domains in which the negotiation sets are never empty are called cooperative domains; in general noncooperative domains, the negotiation set is sometimes empty. This paper presents a theoretical negotiation model for rational agents in general noncooperative domains. Necessary and sufficient conditions for cooperation are outlined. By redefining the concept of utility, it is possible to enlarge the number of situations that have a cooperative solution. An approach is offered for conflict resolution, and it is shown that even in a conflict situation, partial cooperative steps can be taken by interacting agents (that is, agents in fundamental conflict might still agree to cooperate up to a certain point). A unified negotiation protocol (UNP) is developed that can be used in all cases. It is shown that in certain borderline cooperative situations, a partial cooperative agreement (i.e., one that does not achieve all agents' goals) might be preferred by all agents, even though there exists a rational agreement that would achieve all their goals. A “deal hierarchy” is presented that captures the partial order among various kinds of deals between agents. The multiplan deal, which involves negotiating over a pair of joint plans simultaneously, allows cooperative agreement and conflict resolution in both fixed goal and flexible goal domains.
| Original language | English |
|---|---|
| Pages (from-to) | 1317-1324 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Systems, Man and Cybernetics |
| Volume | 21 |
| Issue number | 6 |
| DOIs | |
| State | Published - 1991 |
Bibliographical note
Funding Information:Manuscript received November 11, 1990; revised April 3, 1991. This paper is a revised and expanded version of a paper originally presented at the National Conference on Artificial Intelligence, Boston, MA, July 29-August 3, 1990. This work was supported in part by the Leibniz Center for Research in Computer Science, in part by the Israel National Council for Research and Development (Grant 032-8284), and in part by the Center for Science Absorption, Office of Aliya Absorption, the State of Israel. The authors are with the Computer Science Department, Hebrew University, Givat Ram, Jerusalem, Israel. IEEE Log Number 9102928.