General Video Game AI: Learning from Screen Capture

April 23, 2017 Β· Declared Dead Β· πŸ› IEEE Congress on Evolutionary Computation

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Authors Kamolwan Kunanusont, Simon M. Lucas, Diego Perez-Liebana arXiv ID 1704.06945 Category cs.AI: Artificial Intelligence Citations 20 Venue IEEE Congress on Evolutionary Computation Last Checked 4 months ago
Abstract
General Video Game Artificial Intelligence is a general game playing framework for Artificial General Intelligence research in the video-games domain. In this paper, we propose for the first time a screen capture learning agent for General Video Game AI framework. A Deep Q-Network algorithm was applied and improved to develop an agent capable of learning to play different games in the framework. After testing this algorithm using various games of different categories and difficulty levels, the results suggest that our proposed screen capture learning agent has the potential to learn many different games using only a single learning algorithm.
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