Shivaram Kalyanakrishnan
Shivaram Kalyanakrishnan
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TítuloCitado porAño
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
PAC Subset Selection in Stochastic Multi-armed Bandits.
S Kalyanakrishnan, A Tewari, P Auer, P Stone
ICML 12, 655-662, 2012
Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study, RoboCup 2006: Robot Soccer World Cup X
S Kalyanakrishnan, Y Liu, P Stone
Springer-Verlag, Berlin, Heidelberg, 2006
Information complexity in bandit subset selection
E Kaufmann, S Kalyanakrishnan
Conference on Learning Theory, 228-251, 2013
Batch reinforcement learning in a complex domain
S Kalyanakrishnan, P Stone
Proceedings of the 6th international joint conference on Autonomous agents …, 2007
Efficient Selection of Multiple Bandit Arms: Theory and Practice.
S Kalyanakrishnan, P Stone
ICML 10, 511-518, 2010
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
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
Learning to predict humanoid fall
S Kalyanakrishnan, A Goswami
International Journal of Humanoid Robotics 8 (02), 245-273, 2011
Learning complementary multiagent behaviors: a case study, RoboCup 2009: Robot Soccer world cup XIII
S Kalyanakrishnan, P Stone
Springer-Verlag, Berlin, Heidelberg, 2010
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
An empirical analysis of value function-based and policy search reinforcement learning.
S Kalyanakrishnan, P Stone
AAMAS (2), 749-756, 2009
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
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
Machine learning approach for predicting humanoid robot fall
A Goswami, S Kalyanakrishnan
US Patent 8,554,370, 2013
Characterizing reinforcement learning methods through parameterized learning problems
S Kalyanakrishnan, P Stone
Machine Learning 84 (1-2), 205-247, 2011
PAC identification of a bandit arm relative to a reward quantile
AR Chaudhuri, S Kalyanakrishnan
Thirty-First AAAI Conference on Artificial Intelligence, 2017
Learning methods for sequential decision making with imperfect representations
S Kalyanakrishnan
Three humanoid soccer platforms: Comparison and synthesis
S Kalyanakrishnan, T Hester, M Quinlan, Y Bentor, P Stone
Robot Soccer World Cup, 140-152, 2009
Model-based reinforcement learning in a complex domain
S Kalyanakrishnan, P Stone, Y Liu
Robot Soccer World Cup, 171-183, 2007
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