A Continuous Information Gain Measure to Find the Most Discriminatory Problems for AI Benchmarking

P. C. Mahalanobis, “On the generalized distance in statistics,” National Institute of Science of India , vol. 2, no. 1, pp. 49–55, 1936

1936

Earlier work this paper cites.

T. M. Cover and J. A. Thomas, Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing) . New York, NY, USA: Wiley-Interscience, 2006

2006

Earlier work this paper cites.

J. Carpenter, “May the best analyst win,” Science (New York, N.Y.) , vol. 331, pp. 698–699, 02 2011

2011

Earlier work this paper cites.

A. Weinstein and M. Littman, “Bandit-based planning and learning in continuous-action markov decision processes,” in International Conference on Automated Planning and Scheduling , 2012

2012

Earlier work this paper cites.

M. G. Bellemare, Y. Naddaf, J. Veness, and M. Bowling, “The arcade learning environment: An evaluation platform for general agents,” Journal of Artificial Intelligence Research , vol. 47, pp. 253–279, 2013

2013

Earlier work this paper cites.

M. Ebner, J. Levine, S. Lucas, T. Schaul, T. Thompson, and J. Togelius, “Towards a video game description language,” Artificial and Computational Intelligence in Games , pp. 1–17, 2013

2013

Earlier work this paper cites.

J. Levine, C. Congdon, M. Ebner, G. Kendall, S. Lucas, R. Miikkulainen, T. Schaul, and T. Thompson, “General video game playing,” Artificial and Computational Intelligence in Games , vol. 6, pp. 77–83, 11 2013

2013

Earlier work this paper cites.

T. S. Nielsen, G. A. Barros, J. Togelius, and M. J. Nelson, “Towards generating arcade game rules with VGDL,” in Computational Intelligence and Games (CIG), 2015 IEEE Conference on , 2015, pp. 185–192

Original

2015

Earlier work this paper cites.

D. Perez-Liebana, S. Samothrakis, J. Togelius, T. Schaul, S. M. Lucas, A. Couëtoux, J. Lee, C.-U. Lim, and T. Thompson, “The 2014 general video game playing competition,” IEEE Transactions on Computational Intelligence and AI in Games , vol. 8, no. 3, pp. 229–243, 2016

2016

Cited alongside, same era.

G. Brockman, V. Cheung, L. Pettersson, J. Schneider, J. Schulman, J. Tang, and W. Zaremba, “OpenAI Gym,” CoRR , vol. abs/1606.01540, 2016

Original

2016

Cited alongside, same era.

P. Bontrager, A. Khalifa, A. Mendes, and J. Togelius, “Matching games and algorithms for general video game playing,” in Twelfth Artificial Intelligence and Interactive Digital Entertainment Conference , 2016, pp. 122–128

2016

Cited alongside, same era.

D. J. Soemers, C. F. Sironi, T. Schuster, and M. H. Winands, “Enhancements for real-time Monte-Carlo tree search in general video game playing,” in Computational Intelligence and Games (CIG), 2016 IEEE Conference on , 2016, pp. 1–8

2016

M. J. Nelson, “Investigating vanilla MCTS scaling on the GVG-AI game corpus,” 2016 IEEE Conference on Computational Intelligence and Games (CIG) , pp. 1–7, 2016

2016

Later among the works it cites.

D. Dheeru and E. Karra Taniskidou, “UCI machine learning repository,” http://archive.ics.uci.edu/ml , 2017

2017

Later among the works it cites.

R. D. Gaina, S. M. Lucas, and D. Perez-Liebana, “Rolling horizon evolution enhancements in general video game playing,” in Computational Intelligence and Games (CIG), 2017 IEEE Conference on , 2017, pp. 88–95

2017

Later among the works it cites.

F. Martinez-Plumed and J. Hernandez-Orallo, “Dual indicators to analyse AI benchmarks: Difficulty, discrimination, ability and generality,” IEEE Transactions on Games , pp. 1–1, 2018

2018

Closest in time.

D. Pérez-Liébana, J. Liu, A. Khalifa, R. D. Gaina, J. Togelius, and S. M. Lucas, “General video game AI: a multi-track framework for evaluating agents, games and content generation algorithms,” CoRR , vol. abs/1802.10363, 2018