Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
We present discrete stochastic mathematical models for the growth curves of synchronous and asynchronous evolutionary algorithms with populations structured according to a random ...
Mario Giacobini, Marco Tomassini, Andrea Tettamanz...
The Army’s push towards developing highly flexible military teams that combine manned and unmanned units requires significant advances in the intelligence of the unmanned units ...
Talib S. Hussain, Daniel Cerys, David J. Montana, ...
The paper presents an extension of Vose’s Markov chain model for genetic algorithm (GA). The model contains not only standard genetic operators such as mutation and crossover bu...
Tournament selection is the most frequently used form of selection in genetic programming (GP). Tournament selection chooses individuals uniformly at random from the population. A...