General Video Game AI: Learning from Screen Capture
April 23, 2017 Β· Declared Dead Β· π IEEE Congress on Evolutionary Computation
"No code URL or promise found in abstract"
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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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