| Artificial Intelligence and Life in 2030. One hundred year study on artificial intelligence: Report of the 2015-2016 Study Panel P Stone, R Brooks, E Brynjolfsson, R Calo, O Etzioni, G Hager, ... Stanford University, Stanford, CA, http://ai100. stanford. edu/2016-report …, 2016 | 380* | 2016 |
| PAC Subset Selection in Stochastic Multi-armed Bandits. S Kalyanakrishnan, A Tewari, P Auer, P Stone ICML 12, 655-662, 2012 | 241 | 2012 |
| RoboCup 2006: Robot Soccer World Cup X DG SORRENTI Springer, 2007 | 124* | 2007 |
| Information complexity in bandit subset selection E Kaufmann, S Kalyanakrishnan Conference on Learning Theory, 228-251, 2013 | 115 | 2013 |
| Efficient selection of multiple bandit arms: Theory and practice S Kalyanakrishnan, P Stone ICML, 2010 | 89 | 2010 |
| Batch reinforcement learning in a complex domain S Kalyanakrishnan, P Stone Proceedings of the 6th international joint conference on Autonomous agents …, 2007 | 89 | 2007 |
| UT Austin Villa 2011: a champion agent in the RoboCup 3D soccer simulation competition. P MacAlpine, D Urieli, S Barrett, S Kalyanakrishnan, F Barrera, ... AAMAS, 129-136, 2012 | 50 | 2012 |
| Half field offense: An environment for multiagent learning and ad hoc teamwork M Hausknecht, P Mupparaju, S Subramanian, S Kalyanakrishnan, ... AAMAS Adaptive Learning Agents (ALA) Workshop, 2016 | 48 | 2016 |
| On optimizing interdependent skills: a case study in simulated 3D humanoid robot soccer. D Urieli, P MacAlpine, S Kalyanakrishnan, Y Bentor, P Stone AAMAS 11, 769, 2011 | 47 | 2011 |
| Learning to predict humanoid fall S Kalyanakrishnan, A Goswami International Journal of Humanoid Robotics 8 (02), 245-273, 2011 | 46 | 2011 |
| Direction-changing fall control of humanoid robots: theory and experiments A Goswami, S Yun, U Nagarajan, SH Lee, KK Yin, S Kalyanakrishnan Autonomous Robots 36 (3), 199-223, 2014 | 36 | 2014 |
| RoboCup 2009: Robot Soccer World Cup XIII S Kalyanakrishnan, P Stone, J Baltes Lecture Notes in Computer Science 5949, 153-165, 2010 | 35* | 2010 |
| An empirical analysis of value function-based and policy search reinforcement learning S Kalyanakrishnan, P Stone Proceedings of The 8th International Conference on Autonomous Agents and …, 2009 | 35 | 2009 |
| UT Austin Villa 2011: 3D Simulation Team Report P MacAlpine, D Urieli, S Barrett, F Barrera, A Lopez-Mobilia, V Vu, ... University of Texas at Austin Austin United States, 2011 | 26 | 2011 |
| Machine learning approach for predicting humanoid robot fall A Goswami, S Kalyanakrishnan US Patent 8,554,370, 2013 | 25 | 2013 |
| Characterizing reinforcement learning methods through parameterized learning problems S Kalyanakrishnan, P Stone Machine Learning 84 (1-2), 205-247, 2011 | 22 | 2011 |
| PAC identification of a bandit arm relative to a reward quantile AR Chaudhuri, S Kalyanakrishnan Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 19 | 2017 |
| Learning methods for sequential decision making with imperfect representations S Kalyanakrishnan | 11 | 2011 |
| Three humanoid soccer platforms: Comparison and synthesis S Kalyanakrishnan, T Hester, M Quinlan, Y Bentor, P Stone Robot Soccer World Cup, 140-152, 2009 | 10 | 2009 |
| Model-based reinforcement learning in a complex domain S Kalyanakrishnan, P Stone, Y Liu Robot Soccer World Cup, 171-183, 2007 | 10 | 2007 |
