Defining a Decision-Support Framework in AC3M

Abstract

The prime objective of intelligent agents in Multi-Agent Systems (MAS) is to act. An effective action results from a solid decision-making process. Decision-Support Systems (DSS) are used in MASs to assist in the development of a course of action for an individual or system goal. To ensure decision-making processes between agents remain objective and coherent, coordination model and cooperative problem-solving methodologies need to be implemented. Presently, coordination models have been developed as data-driven, process or control-driven, or hybrid models. Cooperative problem-solving methodologies have been designed to solely focus on allowing agents to share their knowledge which assists in achieving an individual goal or a course of actions. Although coordination and cooperation has been successfully implemented as separate frameworks within intelligent MASs, there is a significant limitation: cognitive modeling within each framework is limited or non-existent. This is a major obstacle within dynamic or unknown environments, as these cognitive environments heavily depend on precise information being made available to make well-informed and instantaneous decisions. This paper shows how the relationship between Belief-Desire-Intention (BDI) and Observe-Orient-Decide-Act (OODA) architectures, coordination and cooperation can promote decision-making processes in MASs. The linking of the decision-making process with coordination and cooperation can ameliorate their lack of cognitive processes. This enhancement is demonstrated by the decision support framework within the Agent Coordination and Cooperation Cognitive Model, or AC3M.