Two variable metric reinforcement learning methods, the natural actor-critic algorithm and the covariance matrix adaptation evolution strategy, are compared on a conceptual level a...
Learning how to make decisions in a domain is a critical aspect of intelligent planning behavior. The ability of a planner to adapt its decision-making to a domain depends in part...
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
Windowing has been proposed as a procedure for efficient memory use in the ID3 decision tree learning algorithm. However, it was shown that it may often lead to a decrease in perf...
We propose an efficient orthonormal wavelet-domain video denoising algorithm based on an appropriate integration of motion compensation into an adapted version of our recently devi...