Journal of Advanced Computational Intelligence and Intelligent Informatics 

About: Journal of Advanced Computational Intelligence and Intelligent Informatics is an academic journal published by Fuji Technology Press Ltd.. The journal publishes majorly in the area(s): Computer science & Fuzzy logic. It has an ISSN identifier of 1883-8014. It is also open access. Over the lifetime, 2348 publications have been published receiving 10904 citations.

Opposition-Based Reinforcement Learning

Abstract: Reinforcement learning is a machine intelligence scheme for learning in highly dynamic, probabilistic environments By interaction with the environment, reinforcement agents learn optimal control policies, especially in the absence of a priori knowledge and/or a sufficiently large amount of training data Despite its advantages, however, reinforcement learning suffers from a major drawback – high calculation cost because convergence to an optimal solution usually requires that all states be visited frequently to ensure that policy is reliable This is not always possible, however, due to the complex, high-dimensional state space in many applications This paper introduces opposition-based reinforcement learning, inspired by opposition-based learning, to speed up convergence Considering opposite actions simultaneously enables individual states to be updated more than once shortening exploration and expediting convergence Three versions of Q-learning algorithm will be given as examples Experimental results for the grid world problem of different sizes demonstrate the superior performance of the proposed approach