Modeling Adaptive Autonomous Agents for Intelligent Robots

Real world problems demand adaptive problem solver that can tailor their behavior to their task domain, both during a problem solving session and over time across a dynamic and unpredictable environment. Otherwise, incomplete knowledge, uncertainty, the presence of uncertainty agents and processes, and hardware failure and imprecision will conspire to cause uncertainty events, mission failure, and possibly damage to the agents. Autonomous agents are systems that inhabit a dynamic, unpredictable environment in which they try to satisfy a set of time dependent goals or motivations. Agents are said to be adaptive if they improve their competence at dealing with these goals based on experience. Research in autonomous agents has brought about a new way of excitement into the field of intelligent robots. This paper demonstrates modeling of adaptive autonomous agents for intelligent robots, and identifies its current limitations and open problems.