To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
— Adaptive Information Filtering seeks a solution to the problem of information overload through a tailored representation of the user’s interests, called user profile, which ...
Abstract—Chip multiprocessors (CMPs) present a unique scenario for software data prefetching with subtle tradeoffs between memory bandwidth and performance. In a shared L2 based ...
In this paper we describe a new class of representations for realvalued parameters called Center of Mass Encoding (CoME). CoME is based on variable length strings, it is self-adap...
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...