An Intelligent Mario Controller Based on Reinforcement Learning

• Main Authors: Chao-Cheng Chen, 陳朝政
• Other Authors: Jyh-Jong Tsay
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/64458818595722087799

碩士 === 國立中正大學 === 資訊工程研究所 === 99 === Artificial Intelligence for computer games is an interesting topic in recently years. In this context, Mario AI Competition modifies a Super Mario Bros game to be a benchmark software for people who program AI controller to direct Mario and make him overcome the different levels. This competition was handled in the IEEE Games Innovation Conference and the IEEE Symposium on Computational Intelligence and Games from 2009. In this paper, we use the Reinforcement Learning which is one of learning mechanisms in Machine Learning area to construct a Mario AI controller that learns from the complex game environment. Then we train the controller to grow stronger for dealing with several difficulties and types of levels. In controller developing phase, we design the states and actions cautiously to reduce the search space and make the Reinforcement Learning become much suitable for the requirement of online learning.