In this paper a combined use of reinforcement learning and simulated annealing is treated. Most of the simulated annealing methods suggest using heuristic temperature bounds as the...
Abstract. While direct, model-free reinforcement learning often performs better than model-based approaches in practice, only the latter have yet supported theoretical guarantees f...
RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...
This paper describes the adaption and application of an algorithm called Feudal Reinforcement Learning to a complex gridworld navigation problem. The algorithm proved to be not ea...
Most existing clustering algorithms cluster highly related data objects such as Web pages and Web users separately. The interrelation among different types of data objects is eith...