We introduce a new algorithm and a new analysis technique that is applicable to a variety of online optimization scenarios, including regret minimization for Lipschitz regret func...
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...
Some domains, such as real-time strategy (RTS) games, pose several challenges to traditional planning and machine learning techniques. In this paper, we present a novel on-line ca...
Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are speci...
Martin V. Butz, Martin Pelikan, Xavier Llorà...