General Video Game AI: Challenges and Applications Abstract: Although AI has excelled at many narrowly defined problems, it is still very
far from achieving human-like performance in terms of solving problems that it was not
specifically programmed for: hence the challenge of artificial general intelligence (AGI)
was developed to foster more general AI research. A promising way to address this is to
pose the challenge of learning to play video games without knowing any details of the
games in advance. In order to study this in a systematic way the General Video Game AI
(http://gvgai.net) competition series was created. This provides an excellent challenge for computational
intelligence and AI methods and initial results indicate often good though somewhat patchy performance from
simulation-based methods such as Monte Carlo Tree Search and Rolling Horizon Evolutionary Algorithms.
Observing where these methods succeed and fail leads to the conclusion that there is still much scope for
further developing algorithms that mix simulation with long-term learning. While running the competitions
we have built up a large set of GVGAI players. This large pool of adaptive players leads on to very appealing
potential applications in automated and semi-automated game design where the player-set can be used to
evaluate novel games and new parameter settings of existing games. Initial explorations of this idea will be
discussed.
Simon Lucas is a professor of Computer Science in the School of Computer Science and Electronic
Engineering at the University of Essex (UK) where he is the Head of School and leads the Game Intelligence
Group. He holds a PhD degree (1991) in Electronics and Computer Science from the University of
Southampton. His main research interests are games, evolutionary computation, and machine learning, and he
has published widely in these fields with over 180 peer-reviewed papers. He is the inventor of the scanning ntuple
classifier, is the founding Editor-in-Chief of the IEEE Transactions on Computational Intelligence and
AI in Games and co-founded the IEEE Conference on Computational Intelligence and Games. His main
research area now is developing and applying computational intelligence techniques to build better game AI,
better games, and provide deep insights into the nature of intelligence.
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