— We consider the task of accurately controlling a complex system, such as autonomously sliding a car sideways into a parking spot. Although certain regions of this domain are ex...
J. Zico Kolter, Christian Plagemann, David T. Jack...
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Policy Reuse is a reinforcement learning technique that efficiently learns a new policy by using past similar learned policies. The Policy Reuse learner improves its exploration b...
Abstract. Action-probabilistic logic programs (ap-programs), a class of probabilistic logic programs, have been applied during the last few years for modeling behaviors of entities...
Gerardo I. Simari, John P. Dickerson, V. S. Subrah...
— A new standpoint on financial time series, without the use of any mathematical model and of probabilistic tools, yields not only a rigorous approach of trends and volatility, ...