This paper deals with content-based image retrieval. When the user is looking for large categories, statistical classification techniques are efficient as soon as the training se...
Matthieu Cord, Philippe Henri Gosselin, Sylvie Phi...
In this work we assume that there is an agent in an unknown environment (domain). This agent has some predefined actions and it can perceive its current state in the environment c...
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorr...