Constructing and Dynamically Maintaining Perspective-based Agent Models for Command and Control Applications in a Multi-Agent Environment

This paper describes a model that explicitly represents the declarative and behavioral knowledge of a goaldriven agent. The developed declarative and the behavioral models allow an agent to reason about itself, other agents, and the environment. The declarative model specifies data and services (capabilities) assigned to an agent while the behavioral model specifies the execution model of an agent (defined as states, transitions between states, and events affecting the transitions). An Extended Statechart (ESC) is used as the execution model. To maintain these models, a selfcontained computational module called the Perspective Modeler is proposed and incorporated into the Sensible Agent Architecture discussed herein. With the Perspective Modeler, a Sensible Agent has the capability to model itself, other agents, and the environment to generate more desirable behaviors. In support of command and control applications, the Perspective Modeler maintains beliefs about very dynamic declarative and behavioral knowledge to 1) provide “what-is” assessments, 2) provide “what-if” assessments given projected events or actions, and 3) support deliberate actions or reactive actions. The Perspective Modeler implementation as a CORBA object within the Sensible Agent Testbed allows distribution of the Perspective Modeler capability across multiple platforms. Additionally, the model representations (while populated with domain-specific information) and algorithms deployed in the Perspective Modeler are domain-independent promoting rapid and flexible integration into application systems.