This paper describes an explanation-based approach lo learning plans despite a computationally intractable domain theory. In this approach, the system learns an initial plan using...
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...