Since its inception, arti cial intelligence has relied upon a theoretical foundation centred around perfect rationality as the desired property of intelligent systems. We argue, a...
Stuart J. Russell, Devika Subramanian, Ronald Parr
Motion planning for mobile agents, such as robots, acting in the physical world is a challenging task, which traditionally concerns safe obstacle avoidance. We are interested in p...
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
1 One of the major challenges of Applied Artificial Intelligence is to provide environments where high level human activities like learning, constructing theories or performing exp...
In this paper we describe a simple model of adaptive agents of different types, represented by Learning Classifier Systems (LCS), which make investment decisions about a risk fre...