Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
Lihong Li, Michael L. Littman, Christopher R. Mans...
Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...
This paper addresses the problem of optimal cooperative spectrum sensing in a cognitive-enabled sensor network where cognitive sensors can cooperate in the sensing of the spectrum...
Hai Ngoc Pham, Yan Zhang, Paal E. Engelstad, Tor S...
Searchers can have problems devising queries that accurately express their, often dynamic, information needs. In this paper we describe an adaptive approach that uses unobtrusive ...