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Michael L. Littman

22 papers · 2005–2024 · 7 venues · across top CS/AI venues

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Achievements

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+9 more ↓ πŸ—ΊοΈ Taxonomy Completionist (42) πŸƒ Academic Marathon Β· Full 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
🌱 Topic Pioneer πŸ† Keyword Champion 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (7) ⚑ Prolific Year Β· Productive πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (100) πŸ“ˆ Trend Setter πŸ’Ž Century Club Β· Bronze

Venues

NeurIPS (7) AAAI (5) IJCAI (3) JMLR (3) ICML (2) ACL (1) RSS (1)

Top co-authors

Kavosh Asadi (5) David Abel (4) Alexander L. Strehl (3) George Konidaris (3) James MacGlashan (2) Anna Harutyunyan (2) Doina Precup (2) Bethany R. Leffler (2) Lihong Li (2) Omer Gottesman (2)

Research topics

Machine Learning (17) Reinforcement Learning (16) Methods (13) Optimization & Theory (12) Artificial Intelligence (11) Learning Types Β· Machine Learning (10) Core AI (9) Deep Learning (6) Applications (4) Core Methods (3) Learning Paradigms (3) Learning Types Β· Deep Learning (3) Natural Language Processing (1) Architectures (1) Bayesian & Probabilistic (1)

Keywords

reinforcement learning (8) markov decision process (5) value function (3) model-based reinforcement learning (3) sample complexity (3) optimal policy (3) model-based learning (2) markov reward (2) temporal difference learning (2) deep reinforcement learning (2) lifelong reinforcement learning (2) continuous control (2) state representation (2) task specification (2) information bottleneck (1) bayesian inference (1) state abstraction (1) markov decision processes (1) transfer learning (1) model probing (1)

Papers

Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy NeurIPS 2024 Evaluation beyond Task Performance: Analyzing Concepts in AlphaZero in Hex NeurIPS 2022 Faster Deep Reinforcement Learning with Slower Online Network NeurIPS 2022 Model-based Lifelong Reinforcement Learning with Bayesian Exploration NeurIPS 2022 On the Expressivity of Markov Reward (Extended Abstract) IJCAI 2022 On the (In)Tractability of Reinforcement Learning for LTL Objectives IJCAI 2022 Deep Radial-Basis Value Functions for Continuous Control AAAI 2021 Lipschitz Lifelong Reinforcement Learning AAAI 2021 On the Expressivity of Markov Reward NeurIPS 2021 Towards Sample Efficient Agents through Algorithmic Alignment (Student Abstract) AAAI 2021 Context-Driven Satirical News Generation ACL 2020 Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning JMLR 2020 State Abstraction as Compression in Apprenticeship Learning AAAI 2019 Theory of Minds: Understanding Behavior in Groups through Inverse Planning AAAI 2019 An Alternative Softmax Operator for Reinforcement Learning ICML 2017 Interactive Learning from Policy-Dependent Human Feedback ICML 2017 Between Imitation and Intention Learning IJCAI 2015 Provably Efficient Learning with Typed Parametric Models JMLR 2009 Reinforcement Learning in Finite MDPs: PAC Analysis JMLR 2009 Multi-resolution Exploration in Continuous Spaces NeurIPS 2008 Online Linear Regression and Its Application to Model-Based Reinforcement Learning NeurIPS 2007 Efficient Exploration With Latent Structure RSS 2005