This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Abstract. Motivated by the analogies to statistical physics, the deterministic annealing (DA) method has successfully been demonstrated in a variety of application. In this paper, ...
Abstract. We present the PathCrawler prototype tool for the automatic generation of test-cases satisfying the rigorous all-paths criterion, with a user-defined limit on the number...
Nicky Williams, Bruno Marre, Patricia Mouy, Muriel...
R-GMA (Relational Grid Monitoring Architecture) [1] is a grid monitoring and information system that provides a global view of data distributed across a grid system. R-GMA creates ...
Rob Byrom, Brian A. Coghlan, Andrew W. Cooke, Rone...