Michael L. Littman
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American computer scientist
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Michael L. Littmancomputer-science Degrees
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#75
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#202
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#90
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#519
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Computer Science
Michael L. Littman's Degrees
- PhD Computer Science Brown University
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Why Is Michael L. Littman Influential?
(Suggest an Edit or Addition)According to Wikipedia, Michael Lederman Littman is a computer scientist, researcher, educator, and author. His research interests focus on reinforcement learning. He is currently a University Professor of Computer Science at Brown University, where he has taught since 2012.
Michael L. Littman's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Reinforcement Learning: A Survey (1996) (7965)
- Planning and Acting in Partially Observable Stochastic Domains (1998) (4258)
- Markov Games as a Framework for Multi-Agent Reinforcement Learning (1994) (2508)
- Measuring praise and criticism: Inference of semantic orientation from association (2003) (1741)
- Activity Recognition from Accelerometer Data (2005) (1615)
- Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach (1993) (817)
- Learning Policies for Partially Observable Environments: Scaling Up (1997) (777)
- Acting Optimally in Partially Observable Stochastic Domains (1994) (747)
- Graphical Models for Game Theory (2001) (671)
- Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms (2000) (641)
- On the Complexity of Solving Markov Decision Problems (1995) (569)
- Predictive Representations of State (2001) (536)
- Interactions between learning and evolution (1991) (513)
- Friend-or-Foe Q-learning in General-Sum Games (2001) (511)
- Incremental Pruning: A Simple, Fast, Exact Method for Partially Observable Markov Decision Processes (1997) (503)
- An analysis of model-based Interval Estimation for Markov Decision Processes (2008) (467)
- PAC model-free reinforcement learning (2006) (453)
- Algorithms for Sequential Decision Making (1996) (424)
- Unsupervised Learning of Semantic Orientation from a Hundred-Billion-Word Corpus (2002) (421)
- Towards a Unified Theory of State Abstraction for MDPs (2006) (395)
- Value-function reinforcement learning in Markov games (2001) (392)
- PAC Generalization Bounds for Co-training (2001) (318)
- Practical trigger-action programming in the smart home (2014) (318)
- Data Visualization With Multidimensional Scaling (2008) (298)
- An object-oriented representation for efficient reinforcement learning (2008) (297)
- Reinforcement Learning in Finite MDPs: PAC Analysis (2009) (288)
- A Generalized Reinforcement-Learning Model: Convergence and Applications (1996) (267)
- Reinforcement learning improves behaviour from evaluative feedback (2015) (259)
- Memoryless policies: theoretical limitations and practical results (1994) (241)
- Knows what it knows: a framework for self-aware learning (2008) (239)
- Automatic Cross-Language Retrieval Using Latent Semantic Indexing (1997) (233)
- The Computational Complexity of Probabilistic Planning (1998) (228)
- PPDDL 1 . 0 : An Extension to PDDL for Expressing Planning Domains with Probabilistic Effects (2004) (216)
- Automatic Cross-Language Information Retrieval Using Latent Semantic Indexing (1998) (213)
- Corpus-based Learning of Analogies and Semantic Relations (2005) (203)
- An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning (2008) (200)
- Trigger-Action Programming in the Wild: An Analysis of 200,000 IFTTT Recipes (2016) (199)
- Bayesian Adaptive Sampling for Variable Selection and Model Averaging (2011) (191)
- Interactive Learning from Policy-Dependent Human Feedback (2017) (183)
- A theoretical analysis of Model-Based Interval Estimation (2005) (182)
- A Bayesian Sampling Approach to Exploration in Reinforcement Learning (2009) (181)
- A Distributed Reinforcement Learning Scheme for Network Routing (1993) (171)
- A Unified Analysis of Value-Function-Based Reinforcement-Learning Algorithms (1999) (171)
- Apprenticeship Learning About Multiple Intentions (2011) (164)
- Combining Independent Modules to Solve Multiple-choice Synonym and Analogy Problems (2003) (164)
- Stochastic Boolean Satisfiability (2001) (161)
- Algorithm Selection using Reinforcement Learning (2000) (161)
- Probabilistic Propositional Planning: Representations and Complexity (1997) (158)
- Analyzing feature generation for value-function approximation (2007) (157)
- A polynomial-time nash equilibrium algorithm for repeated games (2003) (153)
- The First Probabilistic Track of the International Planning Competition (2005) (150)
- An Alternative Softmax Operator for Reinforcement Learning (2016) (144)
- Learning Predictive State Representations (2003) (138)
- Efficient Structure Learning in Factored-State MDPs (2007) (136)
- The Witness Algorithm: Solving Partially Observable Markov Decision Processes (1994) (135)
- Contingent planning under uncertainty via stochastic satisfiability (1999) (130)
- MAXPLAN: A New Approach to Probabilistic Planning (1998) (126)
- Classes of Multiagent Q-learning Dynamics with epsilon-greedy Exploration (2010) (120)
- Exact Solutions to Time-Dependent MDPs (2000) (118)
- Integrating Sample-Based Planning and Model-Based Reinforcement Learning (2010) (116)
- Near Optimal Behavior via Approximate State Abstraction (2016) (116)
- ATTac-2000: an adaptive autonomous bidding agent (2001) (111)
- A tutorial on partially observable Markov decision processes (2009) (104)
- Exploring compact reinforcement-learning representations with linear regression (2009) (103)
- Automatic cross-linguistic information retrieval using latent semantic indexing (2007) (102)
- Abstraction Methods for Game Theoretic Poker (2000) (101)
- Environment-Independent Task Specifications via GLTL (2017) (101)
- Sample-Based Planning for Continuous Action Markov Decision Processes (2011) (100)
- Learning to Select Branching Rules in the DPLL Procedure for Satisfiability (2001) (98)
- Online Linear Regression and Its Application to Model-Based Reinforcement Learning (2007) (97)
- Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning (2015) (93)
- Reinforcement Learning as a Framework for Ethical Decision Making (2016) (93)
- Coordinate to cooperate or compete: Abstract goals and joint intentions in social interaction (2016) (90)
- An interface for navigating clustered document sets returned by queries (1993) (90)
- Altruism in the evolution of communication (1994) (90)
- Cyclic Equilibria in Markov Games (2005) (87)
- Potential-based Shaping in Model-based Reinforcement Learning (2008) (86)
- Generalized Markov Decision Processes: Dynamic-programming and Reinforcement-learning Algorithms (1996) (86)
- A unifying framework for computational reinforcement learning theory (2009) (85)
- Lazy Approximation for Solving Continuous Finite-Horizon MDPs (2005) (84)
- Showing versus doing: Teaching by demonstration (2016) (82)
- Lipschitz Continuity in Model-based Reinforcement Learning (2018) (81)
- Efficient Reinforcement Learning with Relocatable Action Models (2007) (79)
- Efficient dynamic-programming updates in partially observable Markov decision processes (1995) (79)
- Least-Squares Methods in Reinforcement Learning for Control (2002) (78)
- Implicit Negotiation in Repeated Games (2001) (78)
- Efficient Learning of Action Schemas and Web-Service Descriptions (2008) (77)
- Grounding English Commands to Reward Functions (2015) (77)
- Generalization and Scaling in Reinforcement Learning (1989) (75)
- State Abstractions for Lifelong Reinforcement Learning (2018) (74)
- Bandit-Based Planning and Learning in Continuous-Action Markov Decision Processes (2012) (72)
- A probabilistic approach to solving crossword puzzles (2002) (72)
- Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions (2003) (71)
- A Strategy-Aware Technique for Learning Behaviors from Discrete Human Feedback (2014) (69)
- Leading Best-Response Strategies in Repeated Games (2001) (66)
- Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation (2002) (65)
- On the Computational Complexity of Stochastic Controller Optimization in POMDPs (2011) (65)
- Multi-resolution Exploration in Continuous Spaces (2008) (61)
- Social reward shaping in the prisoner's dilemma (2008) (61)
- Mnemotechnics in Second-Language Learning (2012) (61)
- XGvis: Interactive Data Visualization with Multidimensional Scaling (1998) (60)
- An empirical evaluation of interval estimation for Markov decision processes (2004) (59)
- Online exploration in least-squares policy iteration (2009) (59)
- Incremental Model-based Learners With Formal Learning-Time Guarantees (2006) (59)
- Targeting Specific Distributions of Trajectories in MDPs (2006) (58)
- Learning and planning in environments with delayed feedback (2009) (57)
- Automatic 3-Language Cross-Language Information Retrieval with Latent Semantic Indexing (1997) (56)
- Hypertext for the electronic library?: CORE sample results (1991) (56)
- Taggers for Parsers (1996) (53)
- Deep Reinforcement Learning from Policy-Dependent Human Feedback (2019) (52)
- Theory of Minds: Understanding Behavior in Groups Through Inverse Planning (2019) (51)
- Reinforcement learning for autonomic network repair (2004) (51)
- Democratic approximation of lexicographic preference models (2008) (50)
- Policy and Value Transfer in Lifelong Reinforcement Learning (2018) (48)
- Planning with Abstract Markov Decision Processes (2017) (47)
- How Users Interpret Bugs in Trigger-Action Programming (2019) (46)
- PROVERB: The Probabilistic Cruciverbalist (1999) (45)
- Using iterated reasoning to predict opponent strategies (2011) (45)
- Social is special: A normative framework for teaching with and learning from evaluative feedback (2017) (45)
- Supporting informal communication via ephemeral interest groups (1992) (45)
- Planning with predictive state representations (2004) (44)
- Confidence Bands for Roc Curves (2003) (44)
- Experience-efficient learning in associative bandit problems (2006) (44)
- Learning is planning: near Bayes-optimal reinforcement learning via Monte-Carlo tree search (2011) (43)
- Advantages and Limitations of using Successor Features for Transfer in Reinforcement Learning (2017) (41)
- An optimization-based categorization of reinforcement learning environments (1993) (41)
- A Need for Speed: Adapting Agent Action Speed to Improve Task Learning from Non-Expert Humans (2016) (41)
- Initial Experiments in Stochastic Satisfiability (1999) (40)
- Using Caching to Solve Larger Probabilistic Planning Problems (1998) (39)
- DeepMellow: Removing the Need for a Target Network in Deep Q-Learning (2019) (39)
- Open-Loop Planning in Large-Scale Stochastic Domains (2013) (39)
- On the Expressivity of Markov Reward (2021) (39)
- State Abstraction as Compression in Apprenticeship Learning (2019) (38)
- Partially Observable Markov Decision Processes for Artificial Intelligence (1995) (38)
- Approximate Dimension Equalization in Vector-based Information Retrieval (2000) (38)
- Adaptation in Constant Utility Non-Stationary Environments (1991) (38)
- Measuring and Characterizing Generalization in Deep Reinforcement Learning (2018) (37)
- Dimension reduction and its application to model-based exploration in continuous spaces (2010) (36)
- Interactive Data Visualization with Multidimensional Scaling (36)
- ATTac-2001: A Learning, Autonomous Bidding Agent (2002) (36)
- Reinforcement Learning for Algorithm Selection (2000) (35)
- An Efficient Exact Algorithm for Singly Connected Graphical Games (2002) (35)
- Teaching with Rewards and Punishments: Reinforcement or Communication? (2015) (34)
- A Polynomial-time Nash Equilibrium Algorithm for Repeated Stochastic Games (2008) (34)
- Solving Crossword Puzzles as Probabilistic Constraint Satisfaction (1999) (33)
- The Complexity of Plan Existence and Evaluation in Probabilistic Domains (1997) (33)
- Combining independent modules in lexical multiple-choice problems (2004) (32)
- Combating the Compounding-Error Problem with a Multi-step Model (2019) (32)
- An Introduction to Reinforcement Learning (1995) (32)
- Generalizing Apprenticeship Learning across Hypothesis Classes (2010) (31)
- Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report (2022) (31)
- Between Imitation and Intention Learning (2015) (30)
- Selecting the Right Algorithm (2001) (30)
- A statistical method for language-independent representation of the topical content of text segments (2007) (30)
- An Efficient, Exact Algorithm for Solving Tree-Structured Graphical Games (2001) (29)
- The 2006 AAAI Computer Poker Competition (2006) (29)
- Learning something from nothing: Leveraging implicit human feedback strategies (2014) (27)
- Efficient learning of relational models for sequential decision making (2010) (27)
- Collusion rings threaten the integrity of computer science research (2021) (26)
- Integrating machine learning in ad hoc routing: A wireless adaptive routing protocol (2011) (26)
- Provably Efficient Learning with Typed Parametric Models (2009) (26)
- People Teach With Rewards and Punishments as Communication, Not Reinforcements (2019) (26)
- FAucS : An FCC Spectrum Auction Simulator for Autonomous Bidding Agents (2001) (26)
- Mean Actor Critic (2017) (26)
- Value Preserving State-Action Abstractions (2020) (26)
- CORL: A Continuous-state Offset-dynamics Reinforcement Learner (2008) (25)
- A hierarchical approach to efficient reinforcement learning in deterministic domains (2006) (24)
- Planning and Learning in Environments with Delayed Feedback (2007) (24)
- An Instance-Based State Representation for Network Repair (2004) (24)
- Algorithms for Informed Cows (1997) (24)
- Simulations combining evolution and learning (1996) (23)
- Visualizing the embedding of objects in Euclidean space (1992) (22)
- Reward-predictive representations generalize across tasks in reinforcement learning (2019) (21)
- The value of abstraction (2019) (21)
- Successor Features Combine Elements of Model-Free and Model-based Reinforcement Learning (2019) (21)
- Approaching Bayes-optimalilty using Monte-Carlo tree search (2011) (20)
- Training an Agent to Ground Commands with Reward and Punishment (2014) (20)
- Finding Options that Minimize Planning Time (2018) (20)
- A Review of Reinforcement Learning (2000) (18)
- Reducing reinforcement learning to KWIK online regression (2010) (18)
- An Ensemble of Linearly Combined Reinforcement-Learning Agents (2013) (17)
- Learning a Language-Independent Representation for Terms from a Partially Aligned Corpus (1998) (17)
- Covering Number as a Complexity Measure for POMDP Planning and Learning (2012) (17)
- Review: Computer Language Games (2000) (16)
- Prioritized Sweeping Converges to the Optimal Value Function (2008) (16)
- Coco-Q: Learning in Stochastic Games with Side Payments (2013) (16)
- Most Relevant Explanation: computational complexity and approximation methods (2011) (15)
- Lipschitz Lifelong Reinforcement Learning (2020) (15)
- The Cross-Entropy Method Optimizes for Quantiles (2013) (15)
- Effectively Learning from Pedagogical Demonstrations (2018) (15)
- An Empirical Study of Non-Expert Curriculum Design for Machine Learners (2016) (14)
- Learning Lexicographic Preference Models (2010) (14)
- Model Selection's Disparate Impact in Real-World Deep Learning Applications (2021) (14)
- Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, Montreal, Quebec, Canada, June 14-18, 2009 (2009) (14)
- People construct simplified mental representations to plan (2021) (14)
- Self-Enforcing Strategic Demand Reduction (2002) (13)
- Disambiguation by community membership (1990) (13)
- Learning Analogies and Semantic Relations (2003) (13)
- Deep Radial-Basis Value Functions for Continuous Control (2021) (13)
- Broadening student enthusiasm for computer science with a great insights course (2010) (13)
- Equivalence Between Wasserstein and Value-Aware Loss for Model-based Reinforcement Learning (2018) (13)
- Efficient Exploration With Latent Structure (2005) (13)
- Introduction to the special issue on learning and computational game theory (2007) (12)
- Curriculum Design for Machine Learners in Sequential Decision Tasks (2017) (12)
- The Efficiency of Human Cognition Reflects Planned Information Processing (2020) (12)
- Mitigating Planner Overfitting in Model-Based Reinforcement Learning (2018) (12)
- An Efficient Optimal-Equilibrium Algorithm for Two-player Game Trees (2006) (11)
- Communication in action: Planning and interpreting communicative demonstrations. (2021) (11)
- A New Softmax Operator for Reinforcement Learning (2016) (11)
- Evolution of flexibility and rigidity in retaliatory punishment (2017) (11)
- Large-Scale Planning Under Uncertainty : A Survey (1997) (11)
- Quantifying Uncertainty in Batch Personalized Sequential Decision Making (2014) (11)
- Cost-Sensitive Fault Remediation for Autonomic Computing (2003) (11)
- Equivalence Between Wasserstein and Value-Aware Model-based Reinforcement Learning (2018) (11)
- Convergent Actor Critic by Humans (2016) (10)
- Learning to Interpret Natural Language Instructions (2012) (10)
- Inducing Partially Observable Markov Decision Processes (2012) (10)
- Constraint Satisfaction with Probabilistic Preferences on Variable Values (1999) (10)
- Successor Features Support Model-based and Model-free Reinforcement Learning (2019) (10)
- Planning in Reward-Rich Domains via PAC Bandits (2012) (10)
- An Exploration of Asynchronous Data-Parallelism (1990) (10)
- robabilistic Propositional Planning : Representations and Complexity (1999) (9)
- A Novel Benchmark Methodology and Data Repository for Real-life Reinforcement Learning (2009) (9)
- Q-learning in Two-Player Two-Action Games (2009) (9)
- A Cognitive Hierarchy Model Applied to the Lemonade Game (2010) (9)
- Toward Good Abstractions for Lifelong Learning (2017) (9)
- Learning State Abstractions for Transfer in Continuous Control (2020) (9)
- Feature-based Joint Planning and Norm Learning in Collaborative Games (2016) (9)
- A Comparison of Two Corpus-Based Methods for Translingual Information Retrieval (2000) (9)
- Exploration via Model-based Interval Estimation (2004) (8)
- Transfer with Model Features in Reinforcement Learning (2018) (8)
- Efficient Learning of Dynamics Models using Terrain Classification (2008) (8)
- Introduction to the Probabilistic Planning Track (2004) (8)
- Towards a Simple Approach to Multi-step Model-based Reinforcement Learning (2018) (8)
- Autonomous Quadrotor Control with Reinforcement Learning (2010) (8)
- Trace2TAP: Synthesizing Trigger-Action Programs from Traces of Behavior (2020) (8)
- Learning-based route management in wireless ad hoc networks (2008) (7)
- Peer Reviewing Short Answers using Comparative Judgement (2016) (7)
- A framework for modeling population strategies by depth of reasoning (2012) (7)
- Scratchable Devices: User-Friendly Programming for Household Appliances (2011) (7)
- Stochastic Boolean Satis ability (7)
- Solving Crosswords with PROVERB (1999) (7)
- Bandit-Based Solar Panel Control (2018) (7)
- Initial Progress Toward Development of a Voice-Based Computer-Delivered Motivational Intervention for Heavy Drinking College Students: An Experimental Study (2017) (6)
- Communication, Credibility and Negotiation Using a Cognitive Hierarchy Model (2009) (6)
- Adaptive dynamic server placement in MANETs (2005) (6)
- Brittle AI, Causal Confusion, and Bad Mental Models: Challenges and Successes in the XAI Program (2021) (6)
- Removing the Target Network from Deep Q-Networks with the Mellowmax Operator (2019) (6)
- The effects of selection on noisy fitness optimization (2011) (6)
- Randomized strategic demand reduction: getting more by asking for less (2002) (6)
- Introduction to the special issue on empirical evaluations in reinforcement learning (2011) (5)
- Speeding Safely: Multi-Criteria Optimization in Probabilistic Planning (1997) (5)
- Reinforcement Learning for General LTL Objectives Is Intractable (2021) (5)
- Individual predictions matter: Assessing the effect of data ordering in training fine-tuned CNNs for medical imaging (2019) (5)
- Where, When & Which Concepts Does AlphaZero Learn? Lessons from the Game of Hex (2022) (5)
- Translating English to Reward Functions (2014) (5)
- Teaching a Robot Tasks of Arbitrary Complexity via Human Feedback (2020) (5)
- Perception-based generalization in model-based reinforcement learning (2009) (5)
- Modeling Latent Attention Within Neural Networks (2018) (5)
- Expressing Tasks Robustly via Multiple Discount Factors (2015) (4)
- A hierarchy of prescriptive goals for multiagent learning (2007) (4)
- Algorithms for Partially Observable Markov Decision Processes (1994) (4)
- Stackelberg Punishment and Bully-Proofing Autonomous Vehicles (2019) (4)
- Markov Decision Processes (2001) (4)
- Approximate Dimension Reduction at NTCIR (2001) (4)
- Understanding Trigger-Action Programs Through Novel Visualizations of Program Differences (2021) (4)
- On the (In)Tractability of Reinforcement Learning for LTL Objectives (2021) (3)
- Language and Policy Learning from Human-delivered Feedback (2015) (3)
- A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems (2023) (3)
- The Expected-Length Model of Options (2019) (3)
- Control of mental representations in human planning (2021) (3)
- Exploration in Least-Squares Policy Iteration (2008) (3)
- Efficient model-based exploration in continuous state-space environments (2011) (3)
- Automatic 3-language cross-language information retrieval with LSA (1997) (3)
- Hierarchical Reinforcement Learning (2009) (3)
- A Multiple Representation Approach to Learning Dynamical Systems (2007) (3)
- Toward Improving Solar Panel Efficiency using Reinforcement Learning (2017) (3)
- An Efficient Algorithm for Dynamic Programming in Partially Observable Markov Decision Processes (1995) (3)
- Decision trees (2019) (3)
- Rollout-based Game-tree Search Outprunes Traditional Alpha-beta (2012) (3)
- Designing Rewards for Fast Learning (2022) (3)
- Context-Driven Satirical News Generation (2020) (3)
- Task Scoping for Efficient Planning in Open Worlds (Student Abstract) (2020) (3)
- Optimization problems involving collections of dependent objects (2008) (3)
- A Bibliography of Work Related to Reinforcement Learning (1994) (2)
- Applying prerequisite structure inference to adaptive testing (2020) (2)
- Modeling Latent Attention Within Neural Networks (2017) (2)
- Solving for Best Responses in Extensive-Form Games using Reinforcement Learning Methods (2013) (2)
- Deep RBF Value Functions for Continuous Control (2020) (2)
- PAC-MDP Reinforcement Learning with Bayesian Priors (2009) (2)
- The AAAI Fall Symposia (1999) (2)
- Network Security policy framework and Analysis (2011) (2)
- Learning Finite Linear Temporal Logic Specifications with a Specialized Neural Operator (2021) (2)
- Matrix computations for query expansion in information retrieval (2000) (2)
- Explaining Why: How Instructions and User Interfaces Impact Annotator Rationales When Labeling Text Data (2022) (2)
- Efficient Value-Function Approximation via Online Linear Regression (2008) (2)
- Teaching by Intervention: Working Backwards, Undoing Mistakes, or Correcting Mistakes? (2017) (2)
- Who speaks for AI? (2016) (2)
- Model-based Lifelong Reinforcement Learning with Bayesian Exploration (2022) (2)
- Coarse-Grained Smoothness for RL in Metric Spaces (2021) (2)
- Task Scoping: Building Goal-Specific Abstractions for Planning in Complex Domains (2020) (2)
- Ask Me Anything about MOOCs (2017) (2)
- Improving Solar Panel Efficiency Using Reinforcement Learning (2017) (2)
- A new way to search game trees (2012) (2)
- People Do Not Just Plan, They Plan to Plan (2020) (1)
- Lazy Approximation : A New Approach for Solving Continuous Finite-Horizon MDPs (2005) (1)
- ReNeg and Backseat Driver: Learning from Demonstration with Continuous Human Feedback (2019) (1)
- Reinforcement Learning in Finite MDPs : PAC Analysis Reinforcement Learning in Finite MDPs : PAC Analysis (2008) (1)
- Just-in-time and just-in-place deadlock resolution (2007) (1)
- Initial Experiments in Probabilistic Satissability Initial Experiments in Probabilistic Satissability (2007) (1)
- IPC-4 Probabilistic Planning Track : FAQ 0 . 5 September 13 , 2003 (2003) (1)
- Trace2TAP (2020) (1)
- The Impact of Other-Regarding Preferences in a Collection of Non-Zero-Sum Grid Games (2016) (1)
- Proximal Iteration for Deep Reinforcement Learning (2022) (1)
- Generalized Markov Decision Processes : Dynamic-programming and Reinforcement-learningAlgorithmsCsaba Szepesv (2008) (1)
- People Teach with Rewards and Punishments as Communication not Reinforcements (2018) (1)
- SKILL DISCOVERY WITH WELL-DEFINED OBJECTIVES (2019) (1)
- Planning with Conceptual Models Mined from User Behavior (2007) (1)
- Proceedings, Twenty-Sixth International Conference on Machine Learning (2009) (1)
- Generalization in Deep Reinforcement Learning (2018) (1)
- Bad-Policy Density: A Measure of Reinforcement Learning Hardness (2021) (1)
- Learning Generalizable Behavior via Visual Rewrite Rules (2021) (1)
- Learning Approximate Stochastic Transition Models (2017) (1)
- AAAI-2002 Fall Symposium Series (2003) (1)
- IPC 2004 Probabilistic Planning Track: FAQ 0.1 (2004) (1)
- Draft Version: Do Not Cite! Proverb: the Probabilistic Cruciverbalist (2007) (0)
- Stochastic POMDP controllers: How easy to optimize? (2012) (0)
- Teaching Agents with Evaluative Feedback: Communication versus Reward (2015) (0)
- Evolutionary huffman encoding (2018) (0)
- Efficient Apprenticeship Learning with Smart Humans (2010) (0)
- An Empirical Analysis of RL's Drift From Its Behaviorism Roots (2012) (0)
- Contents to Volume 27 (1986) (0)
- IPC-4 Probabilistic Planning Track : FAQ 1 . 01 November 1 , 2003 (2003) (0)
- Structure & Priors in Reinforcement Learning (SPiRL) (2019) (0)
- AAAI-13 Preface (2013) (0)
- On the Expressivity of Markov Reward (Extended Abstract) (2022) (0)
- Does DQN really learn? Exploring adversarial training schemes in Pong (2022) (0)
- Interactive Learning of Environment Dynamics for Sequential Tasks (2019) (0)
- Taggers for Parsers Taggers for Parsers 1 (1996) (0)
- State Abstraction as Compression in Apprenticeship Learning Supplementary Material (2019) (0)
- Reinforcement Learning and Utility-Based Decisions (2006) (0)
- Hard Starting Problems After Not Driving For A Day Or So (2006) (0)
- Maxibook: User-centered Hypertext on an Ascii Terminal (2007) (0)
- Software Engineering of Machine Learning Systems (2023) (0)
- Towards Approximately Optimal Poker (2000) (0)
- Meta-Learning Parameterized Skills (2022) (0)
- Constraint Satisfaction withProbabilistic Preferences on Variable (1999) (0)
- Simple Learning in Moded Non-stationary Environments (0)
- Comparing Global with Disease specific Machine-learned Readmission Prediction Models (2020) (0)
- Context-Driven Satirical Headline Generation (2020) (0)
- Representation and Learning in Computational Game Theory (2003) (0)
- Specifying Behavior Preference with Tiered Reward Functions (2022) (0)
- Computably Continuous Reinforcement-Learning Objectives are PAC-learnable (2023) (0)
- Selecting Context Clozes for Lightweight Reading Compliance (2022) (0)
- Finding Options that Minimize Planning Time (Appendix) (2019) (0)
- Evidence Humans Provide When Explaining Data-Labeling Decisions (2019) (0)
- Meta-Learning Transferable Parameterized Skills (2022) (0)
- Learning Finite Linear Temporal Logic Formulas (2021) (0)
- XGvis : Intera tive Data Visualizationwith Multidimensional S alingAndreas (2001) (0)
- Personalized Education at Scale (2018) (0)
- Convergence of a Human-in-the-Loop Policy-Gradient Algorithm With Eligibility Trace Under Reward, Policy, and Advantage Feedback (2021) (0)
- Reward-Predictive Clustering (2022) (0)
- State Abstractions for Lifelong Reinforcement Learning ( Appendix ) (2018) (0)
- DCS-TR-641 Exploration in Least-Squares Policy Iteration (2008) (0)
- Learning web-service task descriptions from traces (2012) (0)
- A Change Detection Model for Non-Stationary k-Armed Bandit Problems (2006) (0)
- Flexible theft and resolute punishment: Evolutionary dynamics of social behavior among reinforcement-learning agents (2014) (0)
- Avg. Model Size vs. Changes No. Model Size Error vs. Changes No (2011) (0)
- Communication in Action: Planning and Interpreting Communicative Demonstrations (2019) (0)
- Finding Optimal Strategies over Families of Tasks in Reinforcement Learning (2018) (0)
- Deep Q-Network with Proximal Iteration (2021) (0)
- Relocatable Action Models for Autonomous Navigation (2007) (0)
- Evaluation Beyond Task Performance: Analyzing Concepts in AlphaZero in Hex (2022) (0)
- Tutorial: Learning Topics in Game-Theoretic Decision Making (2003) (0)
- Transferable Models for Autonomous Learning (2007) (0)
- Faster Deep Reinforcement Learning with Slower Online Network (2021) (0)
- Reports on the 2004 AAAI Fall Symposia (2005) (0)
- Optimal planning to plan: People partially plan based on plan specificity (2019) (0)
- Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces (2023) (0)
- Making the Intelligent Home Smart Through Touch-Control Trigger-Action Programming (2017) (0)
- Data augmentation and the role of hardness for feature learning in NLP (2020) (0)
- Towards Behavior-Aware Model Learning from Human-Generated Trajectories (2016) (0)
- Reinforcement Learning via Online Linear Regression (2007) (0)
- Puzzle: baffling raffling (2011) (0)
- Inferring the Intentions of Learning Agents (2018) (0)
- Towards Sample Efficient Agents through Algorithmic Alignment (Student Abstract) (2021) (0)
- Approximate Planning in the Probabilistic-Planning-as-Stochastic-Satisfiability Paradigm (2006) (0)
- Model-based Knowledge Representations (2019) (0)
- Acquiring and Exploiting Rich Causal Models for Robust Decision Making (2012) (0)
- The Efficiency of Human Cognition Reflects Planned Use of Information Processing (2019) (0)
- Learning User's Preferred Household Organization via Collaborative Filtering Methods (2016) (0)
- Task Scoping: Generating Task-Specific Abstractions for Planning in Open-Scope Models (2020) (0)
- Helping Users Debug Trigger-Action Programs (2022) (0)
- Appendix: On the Expressivity of Markov Reward (2022) (0)
- Proverb: the Probabilistic Cruciverbalist Proverb: the Probabilistic Cruciverbalist (1999) (0)
- Teaching with IMPACT (2019) (0)
- Autonomous Model Learning for Reinforcement Learning (2008) (0)
- Agent Mediated Electronic Commerce IV : Designing Mechanisms and Systems , Springer Verlag , 2002 . ATTac-2001 : A Learning , Autonomous Bidding Agent (2015) (0)
- Summable Reparameterizations of Wasserstein Critics in the One-Dimensional Setting (2017) (0)
- Sluggish Acceleration Then Later In The Day Dead On The Road. Now No Start (2011) (0)
- Appendix: BFS3 Proof of Optimality (2011) (0)
- PAC Reinforcement Learning in Noisy Continuous Worlds (2008) (0)
- “ Structure & Priors in Reinforcement Learning ” at ICLR 2019 V ALUE P RESERVING S TATE-A CTION A BSTRACTIONS ( A PPENDIX ) (2019) (0)
- IPC-4 Probabilistic Planning Track : FAQ 1 . 0 September 2003 (2003) (0)
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