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Reward-Predictive Clustering


Nov 07, 2022
Lucas Lehnert, Michael J. Frank, Michael L. Littman


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Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report


Oct 27, 2022
Michael L. Littman, Ifeoma Ajunwa, Guy Berger, Craig Boutilier, Morgan Currie, Finale Doshi-Velez, Gillian Hadfield, Michael C. Horowitz, Charles Isbell, Hiroaki Kitano, Karen Levy, Terah Lyons, Melanie Mitchell, Julie Shah, Steven Sloman, Shannon Vallor, Toby Walsh

* 82 pages, https://ai100.stanford.edu/gathering-strength-gathering-storms-one-hundred-year-study-artificial-intelligence-ai100-2021-study 

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Designing Rewards for Fast Learning


May 30, 2022
Henry Sowerby, Zhiyuan Zhou, Michael L. Littman

* To appear at the 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM2022) 

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Deep Q-Network with Proximal Iteration


Dec 10, 2021
Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Michael L. Littman, Alexander J. Smola

* Work in Progress 

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On the Expressivity of Markov Reward


Nov 01, 2021
David Abel, Will Dabney, Anna Harutyunyan, Mark K. Ho, Michael L. Littman, Doina Precup, Satinder Singh

* Accepted to NeurIPS 2021 

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Bad-Policy Density: A Measure of Reinforcement Learning Hardness


Oct 07, 2021
David Abel, Cameron Allen, Dilip Arumugam, D. Ellis Hershkowitz, Michael L. Littman, Lawson L. S. Wong

* Presented at the 2021 ICML Workshop on Reinforcement Learning Theory 

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Convergence of a Human-in-the-Loop Policy-Gradient Algorithm With Eligibility Trace Under Reward, Policy, and Advantage Feedback


Sep 15, 2021
Ishaan Shah, David Halpern, Kavosh Asadi, Michael L. Littman

* Accepted into ICML 2021 workshops Human-AI Collaboration in Sequential Decision-Making and Human in the Loop Learning 

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Brittle AI, Causal Confusion, and Bad Mental Models: Challenges and Successes in the XAI Program


Jun 10, 2021
Jeff Druce, James Niehaus, Vanessa Moody, David Jensen, Michael L. Littman


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Control of mental representations in human planning


May 14, 2021
Mark K. Ho, David Abel, Carlos G. Correa, Michael L. Littman, Jonathan D. Cohen, Thomas L. Griffiths


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Towards Sample Efficient Agents through Algorithmic Alignment


Sep 08, 2020
Mingxuan Li, Michael L. Littman


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