Distributed W-Learning (DWL) is a reinforcement learningbased algorithm for multi-policy optimization in agent-based systems. In this poster we propose the use of DWL for decentra...
—Over the last two decades, many Differential Evolution (DE) strategies have been introduced for solving Optimization Problems. Due to the variability of the characteristics in o...
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
Evolutionary Algorithms (EAs) can be used for designing Particle Swarm Optimization (PSO) algorithms that work, in some cases, considerably better than the human-designed ones. By...
Motion scalability is designed to improve the coding efficiency of a scalable video coding framework, especially in the medium to low range of decoding bit rates or spatial resol...