Satinder Singh

Michael P. Wellman, Quang Duong, Satinder P. Singh, 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

Multi-Stage Attack Graph Security Games: Heuristic Strategies, with Empirical Game-Theoretic Analysis

Michael P. Wellman, Mason Wright, Thanh Hai Nguyen, 2017, MTD@CCS.

Ecologically valid long-term mood monitoring of individuals with bipolar disorder using speech

Emily Mower Provost, Satinder P. Singh, Zahi N. Karam, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Predictive linear-Gaussian models of controlled stochastic dynamical systems

Satinder P. Singh, Matthew R. Rudary, Satinder Singh, 2006, ICML.

Low-Rank Spectral Learning

Alex Kulesza, Satinder P. Singh, N. Raj Rao, 2014, AISTATS.

Computationally Rational Saccadic Control: An Explanation of Spillover Effects Based on Sampling from Noisy Perception and Memory

Richard L. Lewis, Satinder P. Singh, Michael Shvartsman, 2014, CMCL@ACL.

Computing Solutions in Infinite-Horizon Discounted Adversarial Patrolling Games

Bo An, Milind Tambe, Yevgeniy Vorobeychik, 2014, ICAPS.

Distributed Feedback Control for Decision Making on Supply Chains

Michael P. Wellman, Yevgeniy Vorobeychik, Vishal Soni, 2004, ICAPS.

STRATEGIC INTERACTIONS IN A SUPPLY CHAIN GAME

Michael P. Wellman, Yevgeniy Vorobeychik, Vishal Soni, 2005, Comput. Intell..

Where Do Rewards Come From

Richard L. Lewis, Andrew G. Barto, Satinder Singh, 2009 .

Knowledge Combination in Graphical Multiagent Model pdf

Michael P. Wellman, Quang Duong, Satinder P. Singh, 2012, ArXiv.

The Efficient Learning of Multiple Task Sequences

Satinder P. Singh, Satinder Singh, 1991, NIPS.

Value-driven procurement in the TAC supply chain game

Michael P. Wellman, Vishal Soni, Christopher Kiekintveld, 2004, SECO.

Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective

Richard L. Lewis, Andrew G. Barto, Satinder P. Singh, 2010, IEEE Transactions on Autonomous Mental Development.

On the Complexity of Policy Iteration pdf

Yishay Mansour, Satinder P. Singh, Satinder Singh, 1999, UAI.

Using Homomorphisms to Transfer Options across Continuous Reinforcement Learning Domains

Vishal Soni, Satinder P. Singh, Satinder Singh, 2006, AAAI.

Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms

Tommi S. Jaakkola, Csaba Szepesvári, Michael L. Littman, 2000, Machine Learning.

Approximate Planning for Factored POMDPs using Belief State Simplification pdf

David A. McAllester, Satinder P. Singh, Satinder Singh, 1999, UAI.

Cobot: A Social Reinforcement Learning Agent

Peter Stone, Michael Kearns, Christian R. Shelton, 2001, NIPS.

Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms

Michael Kearns, Satinder P. Singh, Satinder Singh, 1998, NIPS.

Cobot in LambdaMOO: An Adaptive Social Statistics Agent

Peter Stone, Michael Kearns, Christian R. Shelton, 2006, Autonomous Agents and Multi-Agent Systems.

Learning Predictive State Representations

Peter Stone, Michael L. Littman, Satinder P. Singh, 2003, ICML.

A social reinforcement learning agent

Peter Stone, Michael Kearns, Christian R. Shelton, 2001, AGENTS '01.

Theoretical Results on Reinforcement Learning with Temporally Abstract Options

Doina Precup, Richard S. Sutton, Satinder P. Singh, 1998, ECML.

Intrinsically Motivated Reinforcement Learning

Nuttapong Chentanez, Andrew G. Barto, Satinder P. Singh, 2004, NIPS.

Repeated Inverse Reinforcement Learning pdf

Nan Jiang, Kareem Amin, Satinder P. Singh, 2017, NIPS.

Asynchronous Modified Policy Iteration with Single-sided Updates

Satinder Singh, 1993 .

Predictive State Representations: A New Theory for Modeling Dynamical Systems pdf

Michael R. James, Satinder P. Singh, Matthew R. Rudary, 2004, UAI.

How to Dynamically Merge Markov Decision Processes

Satinder P. Singh, David Cohn, Satinder Singh, 1997, NIPS.

Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems

Satinder P. Singh, David Wingate, Satinder Singh, 2006, ICML.

Computing approximate bayes-nash equilibria in tree-games of incomplete information

Michael P. Wellman, Vishal Soni, Satinder P. Singh, 2004, EC '04.

Graphical Models for Game Theory

Michael L. Littman, Michael Kearns, Satinder P. Singh, 2001, UAI.

Future Vision for Autonomous Ocean Observations

Brian Polagye, Satinder Singh, Ramasamy Venkatesan, 2020, Frontiers in Marine Science.

Reinforcement Learning for 3 vs. 2 Keepaway

Peter Stone, Richard S. Sutton, Satinder P. Singh, 2000, RoboCup.

An MDP-Based Approach to Online Mechanism Design

David C. Parkes, Satinder P. Singh, Satinder Singh, 2003, NIPS.

Efficient Online Mechanisms for Persistent, Periodically Inaccessible Self-Interested Agents

David C. Parkes, Ruggiero Cavallo, Satinder Singh, 2007 .

Optimizing Admission Control while Ensuring Quality of Service in Multimedia Networks via Reinforcement Learning

Timothy X. Brown, Hui Tong, Satinder P. Singh, 1998, NIPS.

Soft Dynamic Programming Algorithms: Convergence Proofs Soft Dynamic Programming Algorithms: Convergence Proofs

Satinder Singh, 1993 .

Empirical Evaluation of a Reinforcement Learning Spoken Dialogue System

Marilyn A. Walker, Michael Kearns, Diane J. Litman, 2000, AAAI/IAAI.

Transfer via soft homomorphisms

Satinder P. Singh, Jonathan Sorg, Satinder Singh, 2009, AAMAS.

Learning and Predicting Dynamic Behavior with Graphical Multiagent Models

Quang Duong, Satinder Singh, Michael P. Wellman, 2012 .

ATTac-2000: an adaptive autonomous bidding agent

Peter Stone, Michael L. Littman, Satinder P. Singh, 2001, AGENTS '01.

Dynamic Incentive Mechanisms

David C. Parkes, Ruggiero Cavallo, Satinder P. Singh, 2010, AI Mag..

DaNaLIX: a domain-adaptive natural language interface for querying XML

H. V. Jagadish, Huahai Yang, Yunyao Li, 2007, SIGMOD '07.

Commitment Semantics for Sequential Decision Making under Reward Uncertainty

Edmund H. Durfee, Stefan J. Witwicki, Satinder P. Singh, 2016, IJCAI.

Linking Context to Evaluation in the Design of Safety Critical Interfaces

Lance Sherry, Richard L. Lewis, Andrew Howes, 2013, HCI.

Reinforcement Learning for Spoken Dialogue Systems

Marilyn A. Walker, Michael Kearns, Diane J. Litman, 1999, NIPS.

FAucS : An FCC Spectrum Auction Simulator for Autonomous Bidding Agents

Peter Stone, Michael L. Littman, Satinder P. Singh, 2001, WELCOM.

Multistage Attack Graph Security Games: Heuristic Strategies, with Empirical Game-Theoretic Analysis

Michael P. Wellman, Mason Wright, Thanh Hai Nguyen, 2018, Secur. Commun. Networks.

Experimental Results on Learning Stochastic Memoryless Policies for Partially Observable Markov Decision Processes

Satinder P. Singh, John K. Williams, Satinder Singh, 1998, NIPS.

An Adaptive Sensorimotor Network Inspired by the Anatomy and Physiology

James C. Houk, Andrew G. Barto, Satinder Singh, 1989 .

Learning and predicting dynamic networked behavior with graphical multiagent models

Michael P. Wellman, Michael Kearns, Quang Duong, 2012, AAMAS.

Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning

Martha E. Pollack, Satinder P. Singh, Matthew R. Rudary, 2004, ICML.

The Adaptive Nature of Eye Movements in Linguistic Tasks: How Payoff and Architecture Shape Speed-Accuracy Trade-Offs

Richard L. Lewis, Satinder P. Singh, Michael Shvartsman, 2013, Top. Cogn. Sci..

Constraint satisfaction algorithms for graphical games

Michael P. Wellman, Vishal Soni, Satinder P. Singh, 2007, AAMAS '07.

Computing Stackelberg Equilibria in Discounted Stochastic Games

Yevgeniy Vorobeychik, Satinder P. Singh, Satinder Singh, 2012, AAAI.

A Boosting Approach to Topic Spotting on Subdialogues

Marilyn A. Walker, Michael Kearns, Satinder P. Singh, 2000, ICML.

Enabling Domain-Awareness for a Generic Natural Language Interface

H. V. Jagadish, Huahai Yang, Yunyao Li, 2007, AAAI.

Predicting Postoperative Atrial Fibrillation from Independent ECG Components

Zeeshan Syed, Satinder P. Singh, Zahi N. Karam, 2014, AAAI.

Approximate predictive state representations

Michael R. James, Satinder P. Singh, Britton Wolfe, 2008, AAMAS.

Rational use of Episodic and Working Memory: A Normative Account of Prospective Memory

Richard L. Lewis, Jonathan D. Cohen, Satinder Singh, 2019, bioRxiv.

Abstraction Selection in Model-based Reinforcement Learning

Nan Jiang, Alex Kulesza, Satinder P. Singh, 2015, ICML.

Reinforcement Learning with Replacing Eligibility Traces Figure 1. Accumulating and Replacing Eligibility Traces. Reinforcement Learning with Replacing Eligibility Traces 2. Td() and Monte Carlo Prediction Methods 2.2. Monte Carlo Algorithms Reinforcement Learning with Replacing Eligibility Traces 5

Satinder Singh, 1996 .

Reinforcement Learning for 3 vs. 2 Keepaway

R. Sutton, Satinder Singh, P. Stone, 2000, RoboCup.

Learning Without State-Estimation in Partially Observable Markovian Decision Processes

Michael I. Jordan, Tommi S. Jaakkola, Satinder P. Singh, 1994, ICML.

Off-policy Learning with Options and Recognizers

Doina Precup, Richard S. Sutton, Satinder P. Singh, 2005, NIPS.

Transfer of learning by composing solutions of elemental sequential tasks

Satinder Singh, 2004, Machine Learning.

Stochastic Stackelberg games with applications to adversarial patrolling.

Bo An, Milind Tambe, Yevgeniy Vorobeychik, 2012 .

An Upper Bound on the Loss from Approximate Optimal-Value Functions

Satinder Singh, Satinder Singh, R. Yee, 2004, Machine-mediated learning.

Predictive Linear-Gaussian Models of Stochastic Dynamical Systems

Matthew R. Rudary, Satinder Singh, D. Wingate, 2005, UAI.

The Ecient Learning of Multiple Task Sequences

Satinder Singh, 1992 .

Motor programs and sensorimotor integration

Thomas Sinkjær, James C. Houk, Andrew G. Barto, 1990 .

ATTac-2000: An Adaptive Autonomous Bidding Agent

Satinder Singh, M. Littman, P. Stone, 2001, J. Artif. Intell. Res..

Learning and Predicting Dynamic Network Behavior with Graphical Multiagent Models ( Extended Abstract )

Satinder Singh, M. Kearns, M. Wellman, 2011 .

Reinforcement learning for adaptive cognitive orthotics

Martha E. Pollack, Satinder Singh, Matthew R. Rudary, 2004, AAAI 2004.

Rational use of episodic and working memory: A normative account of prospective memory

Richard L. Lewis, Jonathan D. Cohen, Satinder Singh, 2019, Neuropsychologia.

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Satinder Singh, M. Littman, P. Stone, 2007 .

Between MOPs and Semi-MOP: Learning, Planning & Representing Knowledge at Multiple Temporal Scales

Doina Precup, Richard S. Sutton, Samar Singh, 1998 .

Learning curve bounds for a Markov decision process with undiscounted rewards

Lawrence K. Saul, Satinder P. Singh, Satinder Singh, 1996, COLT '96.

Markov decision processes in large state spaces

Lawrence K. Saul, Satinder P. Singh, Satinder Singh, 1995, COLT '95.

On the Computational Economics of Reinforcement Learning

Andrew G. Barto, Satinder Singh, Satinder Singh, 1991 .

Reinforcement Learning with a Hierarchy of Abstract Models

Satinder P. Singh, Satinder Singh, 1992, AAAI.

Learning to Make Predictions In Partially Observable Environments Without a Generative Model

Erik Talvitie, Satinder P. Singh, Satinder Singh, 2011, J. Artif. Intell. Res..

Building Incomplete but Accurate Models

Erik Talvitie, Satinder P. Singh, Britton Wolfe, 2008, ISAIM.

SarsaLandmark: an algorithm for learning in POMDPs with landmarks

Michael R. James, Satinder P. Singh, Satinder Singh, 2009, AAMAS.

Comparing Policy-Gradient Algorithms

Richard S. Sutton, David A. McAllester, Satinder Singh, 2001 .

Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction

Satinder Singh, Satinder Singh, Dilip Arumugam, 2022, Neural Information Processing Systems.

An Experts Algorithm for Transfer Learning

Erik Talvitie, Satinder P. Singh, Satinder Singh, 2007, IJCAI.

Reward Design via Online Gradient Ascent

Richard L. Lewis, Satinder P. Singh, Jonathan Sorg, 2010, NIPS.

Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System pdf

S. Singh, D. Litman, M. Kearns, 2011, J. Artif. Intell. Res..

Efficient Mechanisms with Dynamic Populations and Dynamic Types

David C. Parkes, Ruggiero Cavallo, Satinder Singh, 2009 .

The Dependence of Effective Planning Horizon on Model Accuracy

Nan Jiang, Alex Kulesza, Richard L. Lewis, 2015, AAMAS.

Reinforcement learning of hierarchical skills on the sony aibo robot

Vishal Soni, Satinder Singh, Satinder Singh, 2005, AAAI 2005.

Nash Convergence of Gradient Dynamics in Iterated General-Sum Games pdf

Yishay Mansour, Michael Kearns, Satinder P. Singh, 2013, ArXiv.

Maintaining Predictions over Time without a Model

Erik Talvitie, Satinder P. Singh, Satinder Singh, 2009, IJCAI.

On Structural Properties of MDPs that Bound Loss Due to Shallow Planning

Nan Jiang, Ambuj Tewari, Satinder P. Singh, 2016, IJCAI.

Learning to Communicate and Solve Visual Blocks-World Tasks

Edmund H. Durfee, Richard L. Lewis, Qi Zhang, 2019, AAAI.

Distributed Representation of Limb Motor Programs in Arrays of Adjustable Pattern Generators

Satinder Singh, A. Barto, J. Houk, 1993, Journal of Cognitive Neuroscience.

Where Do Rewards Come From

Richard L. Lewis, Satinder Singh, A. Barto, 2009 .

Completing State Representations using Spectral Learning

Nan Jiang, Alex Kulesza, Satinder P. Singh, 2018, NeurIPS.

Selecting Operator Queries Using Expected Myopic Gain

Edmund H. Durfee, Satinder P. Singh, Robert S. Cohn, 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

On the Convergence of Stochastic Iterative Dynamic Programming Algorithms

Michael I. Jordan, Satinder Singh, T. Jaakkola, 1994, Neural Computation.

PII: S0004-3702(99)00052-1

R. Sutton, Satinder Singh, Doina Precup, 1999 .

Communicating Hierarchical Neural Controllers for Learning Zero-shot Task Generalization

Honglak Lee, Junhyuk Oh, Pushmeet Kohli, 2017 .

Abstraction in Predictive State Representations

Vishal Soni, Satinder P. Singh, Satinder Singh, 2007, AAAI.

Predictive state representations with options

Satinder P. Singh, Britton Wolfe, Satinder Singh, 2006, ICML.

Planning Delayed-Response Queries and Transient Policies under Reward Uncertainty

Edmund H. Durfee, Satinder Singh, Robert Cohn, 2012 .

Reinforcement Learning Algorithms in Markov Decision Processes AAAI-10 Tutorial Part IV: Take home message

Doina Precup, Richard S. Sutton, Csaba Szepesvári, 2010 .

Reinforcement Learning Algorithms in Markov Decision Processes AAAI-10 Tutorial Part II: Learning to predict values

Doina Precup, Richard S. Sutton, Csaba Szepesvári, 2010 .

A Agent Environment StatesActions Rewards Critic B Agent Internal Environment Rewards Critic External Environment Sensations StatesDecisions Actions " Organism "

Satinder Singh, 2005 .

Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems

Satinder Singh, D. Bertsekas, 1996, NIPS.

Improved Switching among Temporally Abstract Actions

R. Sutton, Satinder Singh, Doina Precup, 1998 .

Predictive Linear-Gaussian Models of Stochastic Dynamical Systems

Satinder P. Singh, David Wingate, Matthew R. Rudary, 2005, UAI.

Optimal rewards in multiagent teams

Richard L. Lewis, Shiyin Qin, Satinder P. Singh, 2012, 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL).

Cobot in LambdaMOO: An Adaptive Social Statistics Agent

Satinder Singh, P. Stone, C. Shelton, 2006, Autonomous Agents and Multi-Agent Systems.

Cobot in LambdaMOO : A Social Statistics Agent

Satinder Singh, P. Stone, C. Isbell, 2022 .

Characterizing EVOI-Sufficient k-Response Query Sets in Decision Problems

Edmund H. Durfee, Satinder P. Singh, Robert S. Cohn, 2014, AISTATS.

Intrinsically Motivated Reinforcement Learning

Satinder Singh, A. Barto, N. Chentanez, 2004, NIPS.

Planning with predictive state representations

Michael L. Littman, Michael R. James, Satinder P. Singh, 2004, 2004 International Conference on Machine Learning and Applications, 2004. Proceedings..

Reinforcement Learning Algorithms for Average-Payoff Markovian Decision Processes

Satinder Singh, Recently, Jordan Jaakkola, 1999 .

Semantics and algorithms for trustworthy commitment achievement under model uncertainty

Satinder Singh, E. Durfee, Qi Zhang, 2020, Autonomous Agents and Multi-Agent Systems.

Minimizing Maximum Regret in Commitment Constrained Sequential Decision Making

Edmund H. Durfee, Qi Zhang, Satinder P. Singh, 2017, ICAPS.

Challenges in the Trustworthy Pursuit of Maintenance Commitments Under Uncertainty

Edmund H. Durfee, Qi Zhang, Satinder P. Singh, 2018, TRUST@AAMAS.

Mechanism Design

Satinder Singh, D. Parkes, 2011 .

Computing Stackelberg Equilibria in Discounted Stochastic Games

Satinder Singh, Yevgeniy Vorobeychik, 2012, AAAI.