… Besides, DRL plays an important role in game artificial in… video games, including classical
Arcade games, first-person perspective games and multi-agent real-time strategy games, from …

… used way of connecting agents to reinforcement learning problems. Using this interface, we
… of several deep reinforcement learning algorithms fare on a number of GVGAI games. We …

… deep reinforcement learning in video games. This review starts by discussing the principles
of reinforcement and deep reinforcement … set of research challenges of DRL in video games. …

… for video games with image output, such as too complicated image states to store. In this paper,
an algorithm of deep reinforcement learning(DRL), called Deep … the video games with its …

… As an alternative, we propose to use Deep Reinforcement Learning (Deep RL) to learn …
game engine that are notably an order of magnitude larger than maps typically used in the Deep …

… To reduce the hardware computing resources and training time of deep reinforcement
learning, this study proposed the reinforcement Q-learning-based deep neural network (RQDNN), …

… , deep learning is enabling reinforcement learning (RL) to scale to problems that were
previously intractable, such as learning to play video games … in deep RL, including the deep Q-…

… of recent exciting achievements of deep reinforcement learning (RL). We … video games in
Section 5.1.3. We will see more achievements in imperfect information games and video games…

… in playing games, thus being suitable to explore them looking for bugs. We investigate the
possibility of using RL for load testing video games. Indeed, the goal of game testing is not …

… The objective of this research is to design the deep reinforcement neural learning-based
model that detects the bugs in a game environment. The model automates the bug detection …