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Loftin, Robert, Peng, Bei, MacGlashan, James, Littman, Michael L., Taylor, Matthew E., Huang, Jeff, Roberts, David L.
"Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning." Auton Agent Multi-Agent Syst, vol. 30, no. 1, 2015, pp. 30-59.
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Littman, Michael L.
"Reinforcement learning improves behaviour from evaluative feedback." J. Geophys. Res., vol. 521, no. 7553, 2015, pp. 445-451.
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Loftin, Robert, Peng, Bei, MacGlashan, James, Littman, Michael L., Taylor, Matthew E., Huang, Jeff, Roberts, David L.
"Learning something from nothing: Leveraging implicit human feedback strategies." The 23rd IEEE International Symposium on Robot and Human Interactive Communication, 2014.
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Ur, Blase, McManus, Elyse, Pak Yong Ho, Melwyn, Littman, Michael L.
"Practical trigger-action programming in the smart home." Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI '14, 2014.
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Littman, Michael L.
"A new way to search game trees." Communications of the ACM, vol. 55, no. 3, 2012, pp. 105.
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Vlassis, Nikos, Littman, Michael L., Barber, David.
"On the Computational Complexity of Stochastic Controller Optimization in POMDPs." ACM Transactions on Computation Theory, vol. 4, no. 4, 2012, pp. 1-8.
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Clyde, Merlise A., Ghosh, Joyee, Littman, Michael L.
"Bayesian Adaptive Sampling for Variable Selection and Model Averaging." Journal of Computational and Graphical Statistics, vol. 20, no. 1, 2011, pp. 80-101.
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Yaman, Fusun, Walsh, Thomas J., Littman, Michael L., desJardins, Marie.
"Democratic approximation of lexicographic preference models." Artificial Intelligence, vol. 175, no. 7-8, 2011, pp. 1290-1307.
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Russell, Brian, Littman, Michael L., Trappe, Wade.
"Integrating machine learning in ad hoc routing: A wireless adaptive routing protocol." Int. J. Commun. Syst., vol. 24, no. 7, 2011, pp. 950-966.
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Whiteson, Shimon, Littman, Michael L.
"Introduction to the special issue on empirical evaluations in reinforcement learning." Mach Learn, vol. 84, no. 1-2, 2011, pp. 1-6.
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Yuan, Changhe, Lim, Heejin, Littman, Michael L.
"Most Relevant Explanation: computational complexity and approximation methods." Annals of Mathematics and Artificial Intelligence, vol. 61, no. 3, 2011, pp. 159-183.
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Littman, Michael L., Reeves, Daniel.
"Puzzle." SIGecom Exch., vol. 10, no. 1, 2011, pp. 39-39.
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Ash, Jordan, Babes, Monica, Cohen, Gal, Jalal, Sameen, Lichtenberg, Sam, Littman, Michael, Marivate, Vukosi, Quiza, Phillip, Ur, Blase, Zhang, Emily.
"Scratchable Devices: User-Friendly Programming for Household Appliances." Automata, Languages and Programming, 2011, pp. 137-146.
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Goschin, Sergiu, Littman, Michael L., Ackley, David H.
"The effects of selection on noisy fitness optimization." Proceedings of the 13th annual conference on Genetic and evolutionary computation - GECCO '11, 2011.
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desJardins, Marie, Littman, Michael.
"Broadening student enthusiasm for computer science with a great insights course." Proceedings of the 41st ACM technical symposium on Computer science education - SIGCSE '10, 2010.
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Nouri, Ali, Littman, Michael L.
"Dimension reduction and its application to model-based exploration in continuous spaces." Mach Learn, vol. 81, no. 1, 2010, pp. 85-98.
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Li, Lihong, Littman, Michael L., Walsh, Thomas J., Strehl, Alexander L.
"Knows what it knows: a framework for self-aware learning." Mach Learn, vol. 82, no. 3, 2010, pp. 399-443.
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Li, Lihong, Littman, Michael L.
"Reducing reinforcement learning to KWIK online regression." Annals of Mathematics and Artificial Intelligence, vol. 58, no. 3-4, 2010, pp. 217-237.
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Littman, Michael L.
"A tutorial on partially observable Markov decision processes." Journal of Mathematical Psychology, vol. 53, no. 3, 2009, pp. 119-125.
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Parr, Ronald, Li, Lihong, Taylor, Gavin, Painter-Wakefield, Christopher, Littman, Michael L.
"An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning." Proceedings of the 25th international conference on Machine learning - ICML '08, 2008.
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Strehl, Alexander L., Littman, Michael L.
"An analysis of model-based Interval Estimation for Markov Decision Processes." Journal of Computer and System Sciences, vol. 74, no. 8, 2008, pp. 1309-1331.
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Diuk, Carlos, Cohen, Andre, Littman, Michael L.
"An object-oriented representation for efficient reinforcement learning." Proceedings of the 25th international conference on Machine learning - ICML '08, 2008.
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Littman, Michael.
"Autonomous Model Learning for Reinforcement Learning." 2008 Fifth International Conference on Quantitative Evaluation of Systems, 2008.
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Buja, Andreas, Swayne, Deborah F, Littman, Michael L, Dean, Nathaniel, Hofmann, Heike, Chen, Lisha.
"Data Visualization With Multidimensional Scaling." Journal of Computational and Graphical Statistics, vol. 17, no. 2, 2008, pp. 444-472.
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Yaman, Fusun, Walsh, Thomas J., Littman, Michael L., desJardins, Marie.
"Democratic approximation of lexicographic preference models." Proceedings of the 25th international conference on Machine learning - ICML '08, 2008.
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Li, Lihong, Littman, Michael L., Walsh, Thomas J.
"Knows what it knows." Proceedings of the 25th international conference on Machine learning - ICML '08, 2008.
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Walsh, Thomas J., Nouri, Ali, Li, Lihong, Littman, Michael L.
"Learning and planning in environments with delayed feedback." Auton Agent Multi-Agent Syst, vol. 18, no. 1, 2008, pp. 83-105.
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Roberts, David L., Isbell, Charles L., Littman, Michael L.
"Optimization problems involving collections of dependent objects." Annals of Operations Research, vol. 163, no. 1, 2008, pp. 255-270.
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Zinkevich, Martin, Greenwald, Amy, Littman, Michael L.
"A hierarchy of prescriptive goals for multiagent learning." Artificial Intelligence, vol. 171, no. 7, 2007, pp. 440-447.
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Parr, Ronald, Painter-Wakefield, Christopher, Li, Lihong, Littman, Michael.
"Analyzing feature generation for value-function approximation." Proceedings of the 24th international conference on Machine learning - ICML '07, 2007.
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Walsh, Thomas J., Nouri, Ali, Li, Lihong, Littman, Michael L.
"Planning and Learning in Environments with Delayed Feedback." Automata, Languages and Programming, 2007, pp. 442-453.
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Diuk, Carlos, Strehl, Alexander L., Littman, Michael L.
"A hierarchical approach to efficient reinforcement learning in deterministic domains." Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems - AAMAS '06, 2006.
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Strehl, Alexander L., Mesterharm, Chris, Littman, Michael L., Hirsh, Haym.
"Experience-efficient learning in associative bandit problems." Proceedings of the 23rd international conference on Machine learning - ICML '06, 2006.
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Strehl, Alexander L., Li, Lihong, Wiewiora, Eric, Langford, John, Littman, Michael L.
"PAC model-free reinforcement learning." Proceedings of the 23rd international conference on Machine learning - ICML '06, 2006.
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Littman, Michael L., Stone, Peter.
"A polynomial-time Nash equilibrium algorithm for repeated games." Decision Support Systems, vol. 39, no. 1, 2005, pp. 55-66.
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Strehl, Alexander L., Littman, Michael L.
"A theoretical analysis of Model-Based Interval Estimation." Proceedings of the 22nd international conference on Machine learning - ICML '05, 2005.
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Chadha, R., Poylisher, A., Deb, B., Littman, M., Sabata, B.
"Adaptive Dynamic Server Placement in Manets." MILCOM 2005 - 2005 IEEE Military Communications Conference, 2005.
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Turney, Peter D., Littman, Michael L.
"Corpus-based Learning of Analogies and Semantic Relations." Mach Learn, vol. 60, no. 1-3, 2005, pp. 251-278.
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Strehl, A.L., Littman, M.L.
"An empirical evaluation of interval estimation for Markov decision processes." 16th IEEE International Conference on Tools with Artificial Intelligence, 2004.
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James, M.R., Singh, S., Littman, M.L.
"Planning with predictive state representations." 2004 International Conference on Machine Learning and Applications, 2004. Proceedings., 2004.
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Littman, M.L., Ravi, N., Fenson, E., Howard, R.
"Reinforcement learning for autonomic network repair." International Conference on Autonomic Computing, 2004. Proceedings., 2004.
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