Gene network reconstruction is a multidisciplinary research area involving data mining, machine learning, statistics, ontologies and others. Reconstructed gene network allows us t...
In the recent years, CSP's have come to be seen as the core problem in many applications. We propose here a hybrid algorithm (MC-FC) that combines two different search method...
Abstract. We describe a simple CSP formalism for handling multi-attribute preference problems with hard constraints, one that combines hard constraints and preferences so the two a...
Eugene C. Freuder, Robert Heffernan, Richard J. Wa...
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
In a sampling problem, we are given an input x {0, 1} n , and asked to sample approximately from a probability distribution Dx over poly (n)-bit strings. In a search problem, we ...