An agent-based framework for building decision support systems

TLDR: A functional architecture is described to detect and eliminate all computational redundancies and computational non-redundancy is defined and established as a major goal for the computational model management.

Abstract: This paper proposes a framework for building decision support systems using software agent technology to support organizations characterized by physically distributed, enterprise-wide, heterogeneous information systems. Intelligent agents have offered tremendous potential in supporting well-defined tasks such as information filtering, data mining and data conversion. However, the use of intelligent agents to support decisions has not been explored and merits serious consideration. This paper proposes a taxonomy of agent characteristics that can be used to help identify agents to support different types of decision tasks. We advocate a goal-directed, behavior-based architecture for building cooperative decision support using agents. We look at the development of agent-based DSS as being a process of putting together a coordinated workflow of collaborating agents that is able to support a problem-solving process. The methodology is illustrated by a selection of intelligent agents to support Crisis Action Procedures in a large organization.