Rush 2008
Rush 2008 is a simulator for American Football enhanced for use by artificial intelligence researchers. Based on Rush 2005, it also includes includes minor bugfixes and some adjustments to game physics. Work is underway to release Rush 2008 under an open source license. For more information, contact Matthew Molineaux.
Our video discussing experiments in the Rush simulator, Casey's Quest: Transfer Learning for Adversarial Environments won the Best Video Award at the IJCAI 2009 Artificial Intelligence Video Competition!
Related Publications
- Casey's Quest: Transfer Learning for Adversarial Environments
- Moore, P., Molineaux, M., & Gupta, K.M. (2009). Casey's Quest: Transfer Learning for Adversarial Environments. Video. Appeared at IJCAI-09 AI Video Competition.
- Beating the defense: Using plan recognition to inform learning agents
- Molineaux, M., Aha, D.W., & Sukthankar, G. (2009). Beating the defense: Using plan recognition to inform learning agents. Proceedings of the Twenty-Second International FLAIRS Conference (pp. 337-343). Sanibel Island, FL: AAAI Press.
- Case-Based Reasoning in Transfer Learning
- Aha, D.W., Molineaux, M., & Sukthankar, G. (2009). Case-Based Reasoning in Transfer Learning. Proceedings of the Eighth International Conference on Case-Based Reasoning (pp. 29-44). Seattle, WA: Springer.
- Improving offensive performance through opponent modeling
- Laviers, K., Sukthankar, G., Molineaux, M., & Aha, D.W. (2009). Improving offensive performance through opponent modeling. To appear in Proceedings of the Fifth Conference on Artificial Intelligence and Interactive Digital Entertainment. Stanford, CA: AAAI Press.
- Exploiting early intent recognition for competitive advantage
- Laviers, K., Sukthankar, G., Molineaux, M., & Aha, D.W (2009). Exploiting early intent recognition for competitive advantage. In C. Geib, H. Bui, G. Sukthankar, & D. Pynadath (Eds.) Plan, Activity, and Intent Recognition: Papers from the IJCAI Workshop (Technical Report w28). Pasadena, CA: AAAI Press.
- Opponent modeling and spatial similarity to retrieve and reuse superior plays
- Laviers, K., Sukthankar, G., Klenk, M., Aha, D.W. & Molineaux, M. (2009). Opponent modeling and spatial similarity to retrieve and reuse superior plays. To appear in L. Lamontagne & P. Gonzalez Calero (Eds.) Case-Based Reasoning for Computer Games: Papers from the ICCBR Workshop. Seattle, WA.
- Constructing game agents from video of human behavior (publication reference)
- Li, N., Stracuzzi, D.J., Cleveland, G., Langley, P., Konik, T., Shapiro, D., Ali, K., Molineaux, M., & Aha, D.W. (2009). Constructing game agents from video of human behavior. To appear in Proceedings of the Fifth Conference on Artificial Intelligence and Interactive Digital Entertainment. Stanford, CA: AAAI Press.
- Constructing game agents from video of human behavior (alternate publication)
- Li, N., Stracuzzi, D.J., Cleveland, G., Langley, P., Konik, T., Shapiro, D., Ali, K., Molineaux, M., & Aha, D.W. (2009). Constructing game agents from video of human behavior. To appear in U. Kuter & H. Munoz-Avila (Eds.) Learning Structural Knowledge from Observations: Papers from the IJCAI Workshop (Technical Report WS-09-21). Pasadena, CA: AAAI Press.
- Improving Offensive Performance Through Opponent Modelling
- Laviers, K., Sukthankar, G. (2009). Improving Offensive Performance Through Opponent Modelling. Video. Appeared at IJCAI-09 AI Video Competition.