We describe an effort to train a RoboCup soccer-playing agent playing in the Simulation League using casebased reasoning. The agent learns (builds a case base) by observing the be...
This paper presents a communication-less multi-agent task allocation procedure that allows agents to use past experience to make non-greedy decisions about task assignments. Exper...
As any other problem solving task that employs search, AI Planning needs heuristics to efficiently guide the problem-space exploration. Machine learning (ML) provides several tec...
—Most existing wireless ad hoc routing protocols rely upon the use of backward learning technique with explicit control messages to route packets. In this paper we propose a set ...
Abstract. In this paper, we propose a novel approach for adaptive control of robotic manipulators. Our approach uses a representation of inverse dynamics models learned from a vari...