Compromise in negotiation: exploiting worth functions over states

AbstractPrevious work by G. Zlotkin and J.S. Rosenschein (1989, 1990, 1991, 1992) discussed interagent negotiation protocols. One of the main assumptions there was that the agents' goals remain fixed—the agents cannot relax their initial goals, which can be achieved only as a whole and cannot be partially achieved. A goal there was considered a formula that is either satisfied or not satisfied by a given state.We here present a more general approach to the negotiation problem in non-cooperative domains where agents' goals are not expressed as formulas, but rather as worth functions. An agent associates a particular value with each possible final state; this value reflects the degree of satisfaction the agent derives from being in that state.With this new definition of goal as worth function, an agreement may lead to a situation in which one or both goals are only partially achieved (i.e., agents may not reach their most desired state). We present a negotiation protocol that can be used in a general non-cooperative domain when worth functions are available. This multi-plan deal type allows agents to compromise over their degree of satisfaction, and (in parallel) to negotiate over the joint plan that will be implemented to reach the compromise final state. The ability to compromise often results in a better deal, enabling agents to increase their overall utility.Finally, we present more detailed examples of specific worth functions in various domains, and show how they are used in the negotiation process

Mechanisms for Automated Negotiation in State Oriented Domains

This paper lays part of the groundwork for a domain theory of negotiation, that is, a way of classifying interactions so that it is clear, given a domain, which negotiation mechanisms and strategies are appropriate. We define State Oriented Domains, a general category of interaction. Necessary and sufficient conditions for cooperation are outlined. We use the notion of worth in an altered definition of utility, thus enabling agreements in a wider class of joint-goal reachable situations. 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 types of encounters. 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. Finally, we analyze cases where agents have incomplete information on the goals and worth of other agents. First we consider the case where agents' goals are private information, and we analyze what goal declaration strategies the agents might adopt to increase their utility. Then, we consider the situation where the agents' goals (and therefore stand-alone costs) are common knowledge, but the worth they attach to their goals is private information. We introduce two mechanisms, one 'strict', the other 'tolerant', and analyze their affects on the stability and efficiency of negotiation outcomes.Comment: See http://www.jair.org/ for any accompanying file

An Approach to Analyzing the Need for Meta-Level Communication *

This paper presents an analysis of static and dynamic organizational structures for naturally distributed, homogeneous, cooperative problem solving environments, exemplified by distributed sensor networks. We first show how the performance of any static organization can be statistically described, and then show under what conditions dynamic organizations do better and worse than static ones. Finally, we show how the variance in the agents ' performance leads to uncertainty about whether a dynamic organization will perform better than a static one given only agent a priori expectations. In these cases, we show when meta-level communication about the actual state of problem solving will be useful to agents in constructing a dynamic organizational structure that outperforms a static one. Viewed in its entirety, this paper also presents a methodology for answering questions about the design of distributed problem solving systems by analysis and simulation of the characteristics of a complex environment rather than by relying on single-instance examples.