Much of artificial intelligence research is focused on devising optimal solutions for challenging and well-defined but highly constrained problems. However, as we begin creating...
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
Exploration/Exploitation equilibrium is one of the most challenging issues in reinforcement learning area as well as learning classifier systems such as XCS. In this paper1 , an i...
Self-localisation is an essential competence for mobile robot navigation. Due to the fundamental unreliability of dead reckoning, a robot must depend on its perception of external...
Today user-centered information acquisition over collections of complex XML documents is increasingly in demand. To this end, preferences have become an important paradigm enablin...