Reinforcement Learning Algorithms: Survey and Classification

摘要

Reinforcement Learning (RL) has emerged as a strong approach in the field of Artificial intelligence, specifically, in the field of machine learning, robotic navigation, etc. In this paper we try to do a brief survey on the various RL algorithms, and try to give a perspective on how the trajectory is moving in the research landscape. We are also attempting to classify RL as a 3-D (dimensional) problem, and give a perspective on how the journey of various algorithms in each of these dimensions progressing. We provide a quick recap of basic classifications in RL, and some popular, but old, algorithms. This research paper then discusses some of the recent trends; and also summarizes the entire landscape as can be seen from a bird’s eye view. We provide our perspective in saying that Reinforcement learning is a 3D problem and conclude with challenges that remain ahead of us. We have deliberately kept any deep mathematical equations and concepts out of this paper, as the purpose of this paper is to provide an overview and abstractions to a serious onlooker. We hope this paper provides a brief summary and trends in RL for researchers, students and interested scholars. Keywords: Artificial Intelligence, Cognitive Search, Game Theory, Machine Learning, Reinforcement Learning