Detecting emerging problems in information and manufacturing systems is the goal of monitoring tools. Good and timely detection of problematic conditions from measured indicators ...
As computer systems continue to grow in power and access more networked content and services, we believe there will be an increasing need to provide more user-centric systems that...
Abstract: Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervis...
Abstract. A biologically inspired computational model of rodent representation–based (locale) navigation is presented. The model combines visual input in the form of realistic tw...
Denis Sheynikhovich, Ricardo Chavarriaga, Thomas S...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...