General Game Playing
Most successful game-playing programs, such as the famous chess-playing program Deep Blue, are highly engineered to play a specific game. The challenge of General Game Playing is creating programs that can play new, previously unseen games mainly by analyzing the rules and possibly through small amounts of practice.
Erkin Bahceci Ph.D. Alumni erkin [at] cs utexas edu
Elliot Meyerson Ph.D. Alumni ekm [at] cs utexas edu
Peter Stone Faculty pstone [at] cs utexas edu
Object-Model Transfer in the General Video Game Domain 2016
Alexander Braylan, Risto Miikkulainen, To Appear In Proceedings of the Twelfth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 2016.
Deep Recurrent Q-Learning for Partially Observable MDPs 2015
Matthew Hausknecht and Peter Stone, In AAAI Fall Symposium on Sequential Decision Making for Intelligent Agents (AAAI-SDMIA15), Arlington, Virginia, USA, November 2015.
The Impact of Determinism on Learning Atari 2600 Games 2015
Matthew Hausknecht and Peter Stone, In AAAI Workshop on Learning for General Competency in Video Games, Austin, Texas, USA, January 2015.
A Neuroevolution Approach to General Atari Game Playing 2013
Matthew Hausknecht, Joel Lehman, Risto Miikkulainen, and Peter Stone, IEEE Transactions on Computational Intelligence and AI in Games (2013).
General Game Learning using Knowledge Transfer 2007
Bikramjit Banerjee and Peter Stone, In The 20th International Joint Conference on Artificial Intelligence, pp. 672-677, January 2007.
Graph-Based Domain Mapping for Transfer Learning in General Games 2007
Gregory Kuhlmann and Peter Stone, In Proceedings of the 18th European Conference on Machine Learning, September 2007.
Automatic Heuristic Construction in a Complete General Game Player 2006
Gregory Kuhlmann, Kurt Dresner, and Peter Stone, In Proceedings of the 21st National Conference on Artificial Intelligence, pp. 1457-62, July 2006.
Value Function Transfer for General Game Playing 2006
Bikramjit Banerjee, Gregory Kuhlmann, and Peter Stone, In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.