The desire to make applications and machines more intelligent and the aspiration to enable
their operation without human interaction have been driving innovations in neural networks …

Reinforcement learning (RL) algorithms can successfully solve a wide range of problems
that we faced. Because of the Alpha Go against KeJie in 2017, the topic of RL has reached …

Machine learning is considered as the study of computer algorithms that enables the
machine to learn and adapt to new data without any human intervention. Reinforcement …

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 …

This paper aims to provide a comprehensive survey of the reinforcement learning algorithms
given in the literature. Especially model-free reinforcement learning algorithms are given in …

Reinforcement Learning (RL) is a machine learning (ML) technique to learn sequential
decision-making in complex problems. RL is inspired by trial-and-error based human/animal …

Reinforcement Learning (RL) has proven to be highly effective in various real-world
applications. However, in certain scenarios, Evolutionary Algorithms (EAs) have been …

This article focuses on the recent advances in the field of reinforcement learning (RL) as well
as the present state–of–the–art applications in games. First, we give a general panorama of …

Driven by the recent technological advancements within the field of artificial intelligence
research, deep learning has emerged as a promising representation learning technique …

With the continuous development of information technology, machine intelligence has
become a hot research issue. Deep learning can effectively extract the characteristic …