Integrating real-time AI techniques in adaptive intelligent agents

Abstract

Adaptive intelligent agents pursue multiple goals in dynamic, complex, uncertain environments. Illustrative applications include medical monitoring agents, autonomous robots, and animated actors. Real-time considerations include hard and soft deadlines, as well as more qualitative constraints. There are no bounded-time algorithms for such applications. Agents must construct goal-seeking behavior opportunistically out of component behaviors triggered at runtime. In contrast to conventional real-time systems, an agent's real-time effectiveness cannot be guaranteed by a single provably optimal technique. Instead, it must emerge from interactions among multiple heuristic techniques at architectur, cognition, and control levels.