How an internal observer, that is not given any a priori knowledge or interpretation of what its sensors receives, learn to imitate seems a formidable issue from a viewpoint of a c...
The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments such as RoboCup competitions since othe...
Abstract: Adaptive behavior and learning are required of software agents in many application domains. At the same time agents are often supposed to be resource-bounded systems, whi...
We present tractable, exact algorithms for learning actions' effects and preconditions in partially observable domains. Our algorithms maintain a propositional logical repres...
Models of agent-environment interaction that use predictive state representations (PSRs) have mainly focused on the case of discrete observations and actions. The theory of discre...