Ronald Parr

发表

Improving PAC Exploration Using the Median Of Means

Jonathan P. How, Jason Pazis, Ronald Parr, 2016, NIPS.

Planning Aims for a Network of Horizontal and Overhead Sensors

Ronald Parr, Erik Halvorson, 2008, ISAIM.

Least-Squares Policy Iteration

Michail G. Lagoudakis, Ronald Parr, Ronald E. Parr, 2003, J. Mach. Learn. Res..

Generalized Prioritized Sweeping

David Andre, Nir Friedman, Ronald Parr, 1997, NIPS.

Foundations of Sequential Learning

Kamesh Munagala, Cynthia Rudin, Ronald Parr, 2018 .

Linear Complementarity for Regularized Policy Evaluation and Improvement

Ronald Parr, Jeffrey Johns, Christopher Painter-Wakefield, 2010, NIPS.

Security Games with Multiple Attacker Resources

Vincent Conitzer, Ronald Parr, Dmytro Korzhyk, 2011, IJCAI.

Inference in Hybrid Networks: Theoretical Limits and Practical Algorithms

Uri Lerner, Ronald Parr, Ronald E. Parr, 2001, UAI.

Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems pdf

Ronald Parr, Ronald E. Parr, 1998, UAI.

Reinforcement Learning with Hierarchies of Machines

Stuart J. Russell, Ronald Parr, Ronald E. Parr, 1997, NIPS.

Policy Iteration for Factored MDPs

Daphne Koller, Ronald Parr, Ronald E. Parr, 2000, UAI.

Sample Complexity and Performance Bounds for Non-Parametric Approximate Linear Programming

Jason Pazis, Ronald Parr, 2013, AAAI.

Coordinated Reinforcement Learning

Michail G. Lagoudakis, Carlos Guestrin, Ronald Parr, 2002, ICML.

Kernelized value function approximation for reinforcement learning

Gavin Taylor, Ronald Parr, Ronald E. Parr, 2009, ICML '09.

Approximate Policy Iteration using Large-Margin Classifiers

Michail G. Lagoudakis, Ronald Parr, Ronald E. Parr, 2003, IJCAI.

Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps

Ronald Parr, Austin I. Eliazar, Ronald E. Parr, 2005, NIPS.

Analyzing feature generation for value-function approximation

Lihong Li, Michael L. Littman, Ronald Parr, 2007, ICML '07.

Non-Parametric Approximate Linear Programming for MDPs

Jason Pazis, Ronald Parr, Ronald E. Parr, 2011, AAAI.

XPathLearner: An On-line Self-Tuning Markov Histogram for XML Path Selectivity Estimation

Jeffrey Scott Vitter, Min Wang, Sriram Padmanabhan, 2002, VLDB.

Least-Squares Methods in Reinforcement Learning for Control

Michail G. Lagoudakis, Michael L. Littman, Ronald Parr, 2002, SETN.

DP-SLAM 2.0

Ronald Parr, Austin I. Eliazar, Austin I. Eliazar, 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

Reinforcement Learning as Classification: Leveraging Modern Classifiers

Michail G. Lagoudakis, Ronald Parr, Ronald E. Parr, 2003, ICML.

Approximating Optimal Policies for Partially Observable Stochastic Domains

Stuart J. Russell, Ronald Parr, Ronald E. Parr, 1995, IJCAI.

Fitted Q-Learning for Relational Domains pdf

Kristian Kersting, Kaushik Roy, Sriraam Natarajan, 2020, ArXiv.

Efficient Solution Algorithms for Factored MDPs

Shobha Venkataraman, Carlos Guestrin, Daphne Koller, 2003, J. Artif. Intell. Res..

Efficient Selection of Disambiguating Actions for Stereo Vision pdf

Ronald Parr, Monika Schaeffer, Ronald E. Parr, 2006, UAI.

Dp-slam

Ronald Parr, Austin I. Eliazar, Austin I. Eliazar, 2005 .

Unsupervised discovery of object classes with a mobile robot

Bhaskara Marthi, Ronald Parr, Julian Mason, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning

Lihong Li, Michael L. Littman, Gavin Taylor, 2008, ICML '08.

Learning in Zero-Sum Team Markov Games Using Factored Value Functions

Michail G. Lagoudakis, Ronald Parr, Ronald E. Parr, 2002, NIPS.

PAC Optimal Exploration in Continuous Space Markov Decision Processes

Jason Pazis, Ronald Parr, Ronald E. Parr, 2013, AAAI.

Generalized Value Functions for Large Action Sets

Jason Pazis, Ronald Parr, 2011, ICML.

Solving Stackelberg games with uncertain observability

Vincent Conitzer, Ronald Parr, Dmytro Korzhyk, 2011, AAMAS.

Learning probabilistic motion models for mobile robots

Ronald Parr, Austin I. Eliazar, Ronald E. Parr, 2004, ICML.

Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (2007) pdf

Linda C. van der Gaag, Ronald Parr, 2012, ArXiv.

Max-norm Projections for Factored MDPs

Carlos Guestrin, Daphne Koller, Ronald Parr, 2001, IJCAI.

Model-Free Least-Squares Policy Iteration

Michail G. Lagoudakis, Ronald Parr, Ronald E. Parr, 2001, NIPS.

Making Rational Decisions Using Adaptive Utility Elicitation

Daphne Koller, Ronald Parr, Urszula Chajewska, 2000, AAAI/IAAI.

Efficient Algorithms for Computing Stackelberg Strategies in Security Games

Vincent Conitzer, Ronald Parr, 2012 .

Complexity of Computing Optimal Stackelberg Strategies in Security Resource Allocation Games

Vincent Conitzer, Ronald Parr, Dmytro Korzhyk, 2010, AAAI.

Sparse value function approximation for reinforcement learning

Ronald Parr, Christopher Painter-Wakefield, Ronald E. Parr, 2013 .

Greedy Algorithms for Sparse Reinforcement Learning

Ronald Parr, Christopher Painter-Wakefield, Ronald E. Parr, 2012, ICML.

Efficient approximate policy iteration methods for sequential decision making in reinforcement learning

Michail G. Lagoudakis, Ronald Parr, 2003 .

Value Function Approximation in Noisy Environments Using Locally Smoothed Regularized Approximate Linear Programs pdf

Gavin Taylor, Ronald Parr, Ronald E. Parr, 2012, UAI.

Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes

Marek Petrik, Shlomo Zilberstein, Gavin Taylor, 2010, ICML.

Computing Stackelberg strategies in stochastic games

Vincent Conitzer, Joshua Letchford, Ronald Parr, 2012, SECO.

Value Function Approximation in Zero-Sum Markov Games

Michail G. Lagoudakis, Ronald Parr, Ronald E. Parr, 2002, UAI.

Reinforcement Learning Using Approximate Belief States

Daphne Koller, Ronald Parr, Andres C. Rodriguez, 1999, NIPS.

On-Line Selectivity Estimation for XML Path Expressions using Markov Histograms

Sriram Padmanabhan, Lipyeow Lim, Min Wang, 2005 .

Multi-Step Multi-Sensor Hider-Seeker Games

Vincent Conitzer, Ronald Parr, Erik Halvorson, 2009, IJCAI.

Provably Bounded Optimal Agents

Devika Subramanian, Stuart J. Russell, Ronald Parr, 1993, IJCAI.

Counting Objects with a Combination of Horizontal and Overhead Sensors

Ronald Parr, Erik Halvorson, 2010, Int. J. Robotics Res..

Policy Search via Density Estimation

Andrew Y. Ng, Daphne Koller, Ronald Parr, 1999, NIPS.

Point-Based Policy Iteration

Hui Li, Lawrence Carin, Shihao Ji, 2007, AAAI.

Computing Optimal Strategies to Commit to in Stochastic Games

Vincent Conitzer, Joshua Letchford, Ronald Parr, 2012, AAAI.

Textured occupancy grids for monocular localization without features

Ronald Parr, Julian Mason, Susanna Ricco, 2011, 2011 IEEE International Conference on Robotics and Automation.

DP-SLAM: fast, robust simultaneous localization and mapping without predetermined landmarks

Ronald Parr, Austin I. Eliazar, Ronald E. Parr, 2003, IJCAI 2003.

Object disappearance for object discovery

Bhaskara Marthi, Ronald Parr, Julian Mason, 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Efficient PAC-Optimal Exploration in Concurrent, Continuous State MDPs with Delayed Updates

Jason Pazis, Ronald Parr, Ronald E. Parr, 2016, AAAI.

Computing Factored Value Functions for Policies in Structured MDPs

Daphne Koller, Ronald Parr, Ronald E. Parr, 1999, IJCAI.

Distance Minimization for Reward Learning from Scored Trajectories

Carlo Tomasi, Ronald Parr, Benjamin Burchfiel, 2016, AAAI.

Bayesian Fault Detection and Diagnosis in Dynamic Systems

Gautam Biswas, Uri Lerner, Daphne Koller, 2000, AAAI/IAAI.

Nonmyopic Multiaspect Sensing With Partially Observable Markov Decision Processes

Lawrence Carin, Shihao Ji, Ronald Parr, 2007, IEEE Transactions on Signal Processing.

Multiagent Planning with Factored MDPs

Carlos Guestrin, Daphne Koller, Ronald Parr, 2001, NIPS.

Regionalized Policy Representation for Reinforcement Learning in POMDPs

Hui Li, Lawrence Carin, Ronald Parr, 2007 .

Title Feasibility Study Of Fully Autonomous Vehicles Using Decision-theoretic Control Permalink

Stuart Russell, Ronald Parr, Nikunj Oza, 2000 .