Understanding the Role of Negotiation in Distributed Search Among Heterogeneous Agents Susan E. Lander and Victor R. Lesser Department of Computer Science University of Massachusetts Amherst, MA 01003 {lander,lesser}@cs.umas8.edu Abstract In our research, we explore the role of negotia- tion for conflict resolution in distributed search among heterogeneous and reusable agents. We present negotiated search, an algorithm that ex- plicitly recognizes and exploits conflict to direct search activity across a set of agents. In nego- tiated search, loosely coupled agents interleave the tasks of 1) local search for a solution to some subproblem; 2) integration of local sub- problem solutions into a shared solution; 3) information exchange to define and refine the shared search space of the agents; and 4) assess- ment and reassessment of emerging solutions. Negotiated search is applicable to diverse ap- plication areas and problem-solving environ- ments. It requires only basic search operators and allows maximum flexibility in the distribu- tion of those operators. These qualities make the algorithm particularly appropriate for the integration of heterogeneous agents into appli- cation systems. The algorithm is implemented in a multi-agent framework, TEAM, that provides the infrastructure required for communication and cooperation. 1 Introduction The current state of knowledge-based technology is such that almost every application system is built from scratch. In order to move beyond the prohibitive cost of constantly reinventing, rerepresenting, and reimplement- ing the wheel, researchers are beginning to examine the feasibility of building application systems with reusable agents [Neches et a/., 1991]. A reusable agent is designed to work without a priori knowledge of the agent set in which it will be embedded, instead using a flexible, reac- tive approach to cooperation. Although this flexibility can lead to inefficient problem solving, an agent can of- ten gather information about the agent set as problem solving progresses to improve efficiency. This research was supported by ARPA under ONR Con- tract #N00014-92-J-1698. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. Multi-agent systems do not traditionally acknowledge the role of conflict among agents as a driving force in the control of problem-solving activity. In reusable-agent systems, however, conflict is inevitable since agents are implemented at different times by different people and in different environments. We present a distributed- search algorithm, negotiated search, that uses conflict as a source of control information for directing search ac- tivity across a set of heterogeneous agents in their quest for a mutually acceptable solution. The negotiated-search algorithm has been successfully incorporated into two implemented systems. In [Lan- der and Lesser, 1992b], we describe distributed search in the context of a seven-agent steam condenser de- sign system and discuss how different operator/agent assignments within the negotiated-search algorithm af- fect problem solving. In [Lander and Lesser, 1992a], a two-agent contract negotiation system is presented, and negotiated search is compared to a search strat- egy that is tailored to characteristics of that environ- ment. Through analysis of the environment and search algorithms, we show the versatility and effectiveness of negotiated search in reusable-agent systems while also pointing out that customized search strategies are in- flexible but can improve system performance when they can be applied. In this paper, we describe negotiated search from an application-independent perspective. The need for a flexible algorithm to support reusability and heterogeneity motivates particular aspects of nego- tiated search:  Conflict, negotiation, and democratic determination of acceptability are integral parts of the algorithm.  Agent coordination is accomplished through clearly defined individual roles in the evolution of a shared solution. These roles are realized as operators that accomplish state transitions on shared solutions.  Operators represent standard and widely available search and information-assimilation capabilities. A particular agent may instantiate all defined opera- tors or some subset of defined operators.  Whenever possible, feedback is used to refine the perceived search spaces of individual agents to more closely reflect the true composite search space. TEAM agents are not hostile and will not intentionally 438 Distributed Al