We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...
In this paper we present the theory and practice of co-logic programming (co-LP for brevity), a paradigm that combines both inductive and coinductive logic programming. Co-LP is a ...
Abstract— In this paper, we present an incremental, multiresolution motion planning algorithm designed for systems with differential constraints. Planning for these sytems is mor...
According to the special features of the dynamic heterogeneous grid environment, a loose-coupled and scalable resource model is described by a hybrid multi-level tree reflecting a...
It is believed that quantum computing will begin to have a practical impact in industry around year 2010. We propose an approach to test generation and fault localization for a wi...