Goal-driven Situation Awareness Process Based on Predictive Modeling

Abstract

The increasing complexity of information systems and the inherent limitations of the human mind give rise to the need to delegate the tasks of situation assessment to intelligent agents. Classical models of situation awareness process imply sequential, event-driven treating of situation awareness. However, the recent development in cognitive psychology suggests the central role of predictive, generative modeling in human situational awareness process, which confers advantages when compared with sequential process. This article proposes a goal-driven process and architecture of situational aware intelligent agent based on generative, predictive conceptual modeling. The main advantage is the ability to reuse the rich knowledge about previous experiences, which is constantly updated and kept logically consistent. Similarly to human cognition, such approach allows to reconcile the use of patterns from experience with the information coming from the environment and execution feedback resulting in the updates of those patterns and learning. Compared to the BDI proposed agent architecture adds the ability to dynamically react to the changes in the environment, prioritize those changes in the goal system, reuse and modify beliefs as a consistent pattern system in the knowledge base.