@inproceedings{1dae441b7266461199c4dddf8c255e03,
title = "Reinforcement Learning: A Friendly Introduction",
abstract = "Reinforcement Learning (RL) is a branch of machine learning (ML) that is used to train artificial intelligence (AI) systems and find the optimal solution for problems. This tutorial paper aims to present an introductory overview of the RL. Furthermore, we discuss the most popular algorithms used in RL and the Markov decision process (MDP) usage in the RL environment. Moreover, RL applications and achievements that shine in the world of AI are covered.",
keywords = "Artificial intelligence, Bellman optimality, Markov decision process, Reinforcement learning",
author = "Dema Daoun and Fabiha Ibnat and Zulfikar Alom and Zeyar Aung and Azim, {Mohammad Abdul}",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 2nd International Conference on Deep Learning, Big Data and Blockchain, Deep-BDB 2021 ; Conference date: 23-08-2021 Through 25-08-2021",
year = "2022",
doi = "10.1007/978-3-030-84337-3_11",
language = "British English",
isbn = "9783030843366",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "134--146",
editor = "Irfan Awan and Salima Benbernou and Muhammad Younas and Markus Aleksy",
booktitle = "The International Conference on Deep Learning, Big Data and Blockchain, Deep-BDB 2021",
address = "Germany",
}