Читать книгу Artificial Intelligent Techniques for Wireless Communication and Networking - Группа авторов - Страница 12

P. Anbalagan*, S. Saravanan and R. Saminathan

Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar, India

Abstract

Deep reinforcement learning is a type of machine learning and artificial intelligence in which smart robots, similar to the way people make good decisions, can learn from their actions. Implicit in this form of machine learning is that, depending on their behavior, an agent is rewarded or punished. Including unsupervised machine learning and supervised learning, reinforcement learning is yet another common type of artificial intelligence development. Deep reinforcement learning can lead to incredibly impressive results beyond normal reinforcement learning, due to the fact that it incorporates the core qualities of both deep learning and reinforcement learning. Since this is becoming a very broad and rapidly growing field, the entire application landscape will not be explored, but mainly based on comprehensive and self contained introduction to deep reinforcement learning. The goal of this chapter is twofold: (i) to provide a brief guide to the deep reinforcement learning process; (ii) to present detailed applications and research directions.

Keywords: Artificial intelligence, deep learning, machine learning, reinforcement learning