We study on-line play of repeated matrix games in which the observations of past actions of the other player and the obtained reward are partial and stochastic. We define the Part...
We develop a novel coevolutionary algorithm based upon the concept of Pareto optimality. The Pareto criterion is core to conventional multi-objective optimization (MOO) algorithms....
Abstract. We combine in this paper automatic learning of a large lexicon of semantic concepts with traditional video retrieval methods into a novel approach to narrow the semantic ...
Cees Snoek, Marcel Worring, Dennis Koelma, Arnold ...
While the decision tree is an effective representation that has been used in many domains, a tree can often encode a concept inefficiently. This happens when the tree has to repres...
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...