- Constraint Satisfaction Algorithms for Graphical Games Vishal Soni, Satinder Singh, and Michael P. Wellman
- Machine Learning, 8, 323-339 (1992) 1992 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Near-Optimal Reinforcement Learning in Polynomial Time Michael Kearns
- Strategic Procurement in TAC/SCM: An Empirical Game-Theoretic Analysis Joshua Estelle, Yevgeniy Vorobeychik, Michael P. Wellman, Satinder Singh,
- Hierarchical Optimal Control of MDPs Amy McGovern
- ``BiasVariance'' Error Bounds for Temporal Difference Updates
- FiniteSample Convergence Rates for QLearning and Indirect Algorithms
- Analytical Mean Squared Error Curves in Temporal Difference Learning
- On the Computational Economics of Reinforcement Learning Andrew G. Barto
- Eligibility Traces for OffPolicy Policy Evaluation Doina Precup DPRECUP@CS.UMASS.EDU
- Asynchronous Modified Policy Iteration with Singlesided Updates
- Maintaining Predictions Over Time Without a Model Erik Talvitie
- A Boosting Approach to Topic Spotting on Subdialogues Kary Myers KARY@CS.CMU.EDU
- Auton Agent Multi-Agent Syst DOI 10.1007/s10458-006-0005-z
- Optimal Rewards versus Leaf-Evaluation Heuristics in Planning Agents Jonathan Sorg
- Off-policy Learning with Recognizers Doina Precup
- Predicting Lifetimes in Dynamically Allocated Memory
- Planning with Predictive State Representations Michael R. James
- Efficiently Learning Linear-Linear Exponential Family Predictive Representations of State
- Internal Rewards Mitigate Agent Boundedness Jonathan Sorg jdsorg@umich.edu
- Reward Design via Online Gradient Ascent Jonathan Sorg
- Where Do Rewards Come From? Satinder Singh
- Empirical Evaluation of a Reinforcement Learning Spoken Dialogue System Satinder Singh and Michael Kearns and Diane J. Litman and Marilyn A. Walker
- Reinforcement Learning for 3 vs. 2 Keepaway Peter Stone, Richard S. Sutton, and Satinder Singh
- Long Term Potentiation, Navigation & Dynamic Progamming Peter Dayan
- Between MDPs and SemiMDPs: A Framework for Temporal Abstraction
- As appears in Neural Information Processing Systems 4, pp. 251258, 1992. The Efficient Learning of Multiple Task
- Modeling Multiple-mode Systems with Predictive State Representations Britton Wolfe
- Building Incomplete but Accurate Models Erik Talvitie, Britton Wolfe and Satinder Singh
- Approximate Predictive State Representations Britton Wolfe
- Relational Knowledge with Predictive State Representations David Wingate, Vishal Soni, Britton Wolfe and Satinder Singh
- Exponential Family Predictive Representations of State
- Mixtures of Predictive Linear Gaussian Models for Nonlinear Stochastic Dynamical Systems
- Reinforcement Learning of Hierarchical Skills on the Sony Aibo robot
- Predictive Linear-Gaussian Models of Stochastic Dynamical Systems Matthew Rudary Satinder Singh
- Learning and Discovery of Predictive State Representations in Dynamical Systems with Reset
- Journal of Arti cial Intelligence Research ? 2000 ?? Submitted ??; published ?? Optimizing Dialogue Management with Reinforcement
- Predictive Representations of State Michael L. Littman
- Graphical Models for Game Theory Michael Kearns
- Cobot: A Social Reinforcement Learning Agent Charles Lee Isbell, Jr. Christian R. Shelton
- A Boosting Approach to Topic Spotting on Subdialogues Kary Myers KARY@CS.CMU.EDU
- Eligibility Traces for Off-Policy Policy Evaluation Doina Precup DPRECUP@CS.UMASS.EDU
- Policy Gradient Methods for Reinforcement Learning with Function
- o 8 multi-step options
- Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes
- How to Dynamically Merge Markov Decision Processes
- Reinforcement Learning with Soft State Aggregation
- Reinforcement Learning Algorithm for Partially Observable Markov Decision
- On-line Error in Relative Values Algorithm 1
- Distributed Representation of Limb Motor Programs in Arrays of Adjustable
- CobotDS: A Spoken Dialogue System for Chat Michael Kearnsy, Charles Isbelly, Satinder Singhy, Diane Litmany, Jessica Howez
- NearOptimal Reinforcement Learning in Polynomial Time Michael Kearns
- How to Dynamically Merge Markov Decision Processes
- , , 1--38 () # Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- LEARNING TO SOLVE MARKOVIAN DECISION A Dissertation Presented
- Planning in Models that Combine Memory with Predictive Representations of Michael R. James and Satinder Singh
- Learning Predictive State Representations in Dynamical Systems Without Reset
- Simple Local Models for Complex Dynamical Systems Erik Talvitie
- Reinforcement Learning for Spoken Dialogue Systems
- Learning Without State-Estimation in Partially Observable Markovian Decision Processes
- Near-Optimal Reinforcement Learning in Polynomial Time
- Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes
- CobotDS: A Spoken Dialogue System for Chat Michael Kearnsy, Charles Isbelly, Satinder Singhy, Diane Litmany, Jessica Howez
- Predictive Linear-Gaussian Models of Controlled Stochastic Dynamical Systems
- Linear Options Jonathan Sorg
- Transfer via Soft Homomorphisms Jonathan Sorg
- Approximate Planning for Factored POMDPs using Belief State Simplification
- Planning with ClosedLoop Macro Actions Doina Precup
- As appears in the Proceedings of the Twelth National Conference on Artificial Intelligence, pp. 202207, 1994. Reinforcement Learning Algorithms
- Transfer of Learning Across Compositions of Sequential Tasks Satinder P. Singh
- A Social Reinforcement Learning Agent Charles Lee Isbell, Jr. Christian R. Shelton
- Knowledge Combination in Graphical Multiagent Models Quang Duong Michael P. Wellman
- Empirical Game-Theoretic Analysis of Chaturanga Christopher Kiekintveld, Michael P. Wellman, and Satinder Singh
- Cobot in LambdaMOO: A Social Statistics Agent Charles Lee Isbell, Jr. Michael Kearns
- Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone
- FAucS: An FCC Spectrum Auction Simulator for Autonomous Bidding Agents
- Using Homomorphisms to Transfer Options across Continuous Reinforcement Learning Domains
- Adaptive Cognitive Orthotics: Combining Reinforcement Learning and Constraint-Based Temporal Reasoning
- An Upper Bound on the Loss from Approximate OptimalValue Functions
- An Experts Algorithm for Transfer Learning Erik Talvitie and Satinder Singh
- Cobot in LambdaMOO: A Social Statistics Agent Charles Lee Isbell, Jr. Michael Kearns
- Automatic Optimization of Dialogue Management (COLING submission number 750)
- Soft Dynamic Programming Algorithms: Convergence Proofs
- An (almost) Tutorial on Reinforcement Satinder P. Singh
- Cobot: A Social Reinforcement Learning Agent Charles Lee Isbell, Jr. Christian R. Shelton
- Improving Policies without Measuring Peter Dayan
- Nash Convergence of Gradient Dynamics in GeneralSum Games Satinder Singh
- Predicting Lifetimes in Dynamically Allocated Memory
- Predictive Linear-Gaussian Models of Stochastic Dynamical Systems with Vector-Valued Actions and Observations
- Predictive State Representations: A New Theory for Modeling Dynamical Systems
- Predictive State Representations with Options Britton Wolfe bdwolfe@umich.edu
- Draft: Please do not distribute Learning Predictive State Representations
- SarsaLandmark: An Algorithm for Learning in POMDPs with Landmarks
- Full Backups Sample Backups
- Selecting Operator Queries using Expected Myopic Gain Robert Cohn, Michael Maxim, Edmund Durfee, and Satinder Singh
- Machine Learning, 16,227-233 (1994) 1994 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Draft: Please do not distribute A Nonlinear Predictive State Representation
- Improved Switching among Temporally Abstract Richard S. Sutton
- Empirical Evaluation of a Reinforcement Learning Spoken Dialogue System Satinder Singh and Michael Kearns and Diane J. Litman and Marilyn A. Walker
- Machine Learning, ?, 1?? (1996) fl 1996 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Hierarchical Optimal Control of MDPs Amy McGovern
- Robust Reinforcement Learning in Motion Planning
- Transfer of Learning by Composing Solutions of Elemental Sequential Tasks
- An Ecient Exact Algorithm for Singly Connected Graphical Games
- Learning Graphical Game Models Quang Duong
- Combining Memory and Landmarks with Predictive State Representations Michael R. James and Britton Wolfe and Satinder Singh
- FAucS: An FCC Spectrum Auction Simulator for Autonomous Bidding Agents
- IntraOption Learning about Temporally Abstract Richard S. Sutton, Doina Precup
- Learning Curve Bounds for Markov Decision Processes with Undiscounted Rewards
- To appear in NIPS 1998 Optimizing admission control while ensuring
- As appeared in the Proceedings of the Ninth Machine Learning Conference, pp. 406415. 1992. Scaling Reinforcement Learning Algorithms by Learning Variable
- Reinforcement Learning Algorithm for Partially Observable Markov Decision
- Learning Payoff Functions in Infinite Games Yevgeniy Vorobeychik, Michael P. Wellman, and Satinder Singh
- Intra-Option Learning about Temporally Abstract Richard S. Sutton, Doina Precup
- Graphical Models for Game Theory Michael Kearns
- Reinforcement Learning for Spoken Dialogue Systems
- Dynamic Incentive Mechanisms David C. Parkes
- Long Term Potentiation, Navigation & Dynamic Progamming Peter Dayan
- History-Dependent Graphical Multiagent Models Quang Duong
- On Discovery and Learning of Models with Predictive Representations of State for
- , , 138 () c Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Predictive Representations of State Michael L. Littman
- Journal of Arti cial Intelligence Research 15 (2001) ?-? Submitted 2/01; published 9/01 ATTac-2000: An Adaptive Autonomous Bidding Agent
- As appeared in the Proceedings of the Eighth Yale Workshop on Adaptive and Learning Systems, pp. 9196. Center for Systems Science, Yale University, 1994.
- Theoretical Results on Reinforcement Learning with Temporally Abstract Behaviors
- Markov Decision Processes in Large State Spaces Lawrence K. Saul and Satinder P. Singh
- Fast Planning in Stochastic Games Michael Kearns
- How to Make Software Agents Do the Right Thing
- Mach Learn (2007) 67:145168 DOI 10.1007/s10994-007-0715-8
- Journal of Artificial Intelligence Research ? (2000) ?? Submitted ??; published ?? Optimizing Dialogue Management with Reinforcement
- ATTac2000: An Adaptive Autonomous Bidding Agent Peter Stone, Michael L. Littman, Satinder Singh, Michael Kearns
- Draft: Please do not distribute Learning Predictive State Representations
- Learning Without StateEstimation in Partially Observable Markovian Decision Processes
- On the Complexity of Policy Iteration Yishay Mansour \Lambda and Satinder Singh
- Reinforcement Learning with a Hierarchy of Abstract Models
- Strategic Interactions in a Supply Chain Game Michael P. Wellman Joshua Estelle Satinder Singh
- "Bias-Variance" Error Bounds for Temporal Difference Updates
- Strategic Interactions in the TAC 2003 Supply Chain Joshua Estelle, Yevgeniy Vorobeychik, Michael P. Wellman, Satinder Singh,
- A Social Reinforcement Learning Agent Charles Lee Isbell, Jr. Christian R. Shelton
- Reinforcement Learning with Soft State Aggregation
- On the Convergence of Stochastic Iterative Dynamic Programming Algorithms \Lambda
- Convergence Results for SingleStep OnPolicy ReinforcementLearning Algorithms
- Optimal Coordinated Planning Amongst Self-Interested Agents with Private State
- Optimal Coordination of Loosely-Coupled Self-Interested Robots Ruggiero Cavallo
- Kernel Predictive Linear Gaussian Models for Nonlinear Stochastic Dynamical Systems
- Learning and Predicting Dynamic Behavior with Graphical Multiagent Models
- Comparing Action-Query Strategies in Semi-Autonomous Agents Robert Cohn
- Comparing Action-Query Strategies in Semi-Autonomous (Extended Abstract)
- Learning and Predicting Dynamic Network Behavior with Graphical Multiagent Models
- Modeling Information Diffusion in Networks with Unobserved Links
- Journal of Artificial Intelligence Research 42 (2011) 353-392 Submitted 5/11; published 11/11 Learning to Make Predictions In Partially Observable
