Autonomous agents in snake game via deep reinforcement learning

• Main Authors: WEI, Zhepei, WANG, Di, ZHANG, Ming, TAN, Ah-hwee, MIAO, Chunyan, ZHOU, You
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Deep reinforcement learning; Snake Game; autonomous agent; experience replay; Databases and Information Systems; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/6073; https://ink.library.smu.edu.sg/context/sis_research/article/7076/viewcontent/ICA2018SnakeGame.pdf
• Institution: Singapore Management University

Since DeepMind pioneered a deep reinforcement learning (DRL) model to play the Atari games, DRL has become a commonly adopted method to enable the agents to learn complex control policies in various video games. However, similar approaches may still need to be improved when applied to more challengi...