Advances in Artificial Intelligence / Lecture Notes in Computer Science Bd.4509 (PDF)

Modeling Role-Based Agent Team* (p. 12)
1 Introduction
Teamwork is becoming increasingly important in many dynamic multi-agent systems [13]. Agents in a team need to form joint mental states which drive agents to act together as a team and form the interactions leading their individual actions to team efforts [5, 7]. To simulate teamwork, a teamwork language is demanded to explicitly express the mental states underlying teamwork. In our opinion, the effective design of a teamwork language requires two aspects to consider. First, it should be able to handle unexpected uncertainties occurred in complex and dynamic domains, such as dynamic changes in team’s goals, team members’ unexpected failures to fulfill their responsibilities, decision-making in dynamic environment, and dynamically backing up other team members.

Second, considering the perspective of software engineering, the teamwork language would better allow specify teamwork knowledge conceptually for being reused, particularly, team plans are better specified in terms of abstract entities, instead of specific agents, so as to be reused by different teams of agents. A lower level of abstraction, role, is currently used by many researcher of multiagent systems to close this gap [14, 9, 11, 6, 16]. Biddle and Thomas’s role theory views role as the concept of partitioning behaviors and emphasizing coordination and cooperation [2].

Becht’s ROPE (Role Oriented Programming Environment for multiagent systems) uses roles to decouple the organization of agents from the structure of cooperation processes [1]. Cooperation process is designed from a global perspective and largely independent of concrete agents so that shifting cooperative behavior does not require changing agents (agents can fill multiple roles and switch between them). Stone and Veloso introduced roles as a mechanism for specifying an agent’s internal and external behaviors and