Leslie Pack Kaelbling

Orcid: 0000-0001-6054-7145

Affiliations:
  • MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, USA


According to our database1, Leslie Pack Kaelbling authored at least 244 papers between 1986 and 2024.

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Bibliography

2024
Practice Makes Perfect: Planning to Learn Skill Parameter Policies.
CoRR, 2024

Compositional Generative Modeling: A Single Model is Not All You Need.
CoRR, 2024

Generalized Planning in PDDL Domains with Pretrained Large Language Models.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Video Language Planning.
CoRR, 2023

Embodied Lifelong Learning for Task and Motion Planning.
CoRR, 2023

DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability.
CoRR, 2023

PDSketch: Integrated Planning Domain Programming and Learning.
CoRR, 2023

On the Expressiveness and Generalization of Hypergraph Neural Networks.
CoRR, 2023

Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

What Planning Problems Can A Relational Neural Network Solve?
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Compositional Foundation Models for Hierarchical Planning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Visibility-Aware Navigation Among Movable Obstacles.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Task-Directed Exploration in Continuous POMDPs for Robotic Manipulation of Articulated Objects.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Local Neural Descriptor Fields: Locally Conditioned Object Representations for Manipulation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Compositional Diffusion-Based Continuous Constraint Solvers.
Proceedings of the Conference on Robot Learning, 2023

Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation.
Proceedings of the Conference on Robot Learning, 2023

Embodied Lifelong Learning for Task and Motion Planning.
Proceedings of the Conference on Robot Learning, 2023

Learning Reusable Manipulation Strategies.
Proceedings of the Conference on Robot Learning, 2023

Learning Efficient Abstract Planning Models that Choose What to Predict.
Proceedings of the Conference on Robot Learning, 2023

Predicate Invention for Bilevel Planning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Learning Rational Subgoals from Demonstrations and Instructions.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Representation, learning, and planning algorithms for geometric task and motion planning.
Int. J. Robotics Res., 2022

SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields.
CoRR, 2022

Learning Operators with Ignore Effects for Bilevel Planning in Continuous Domains.
CoRR, 2022

Inventing Relational State and Action Abstractions for Effective and Efficient Bilevel Planning.
CoRR, 2022

PDSketch: Integrated Domain Programming, Learning, and Planning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sparse and Local Networks for Hypergraph Reasoning.
Proceedings of the Learning on Graphs Conference, 2022

Learning Object-Based State Estimators for Household Robots.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Learning Neuro-Symbolic Relational Transition Models for Bilevel Planning.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

PG3: Policy-Guided Planning for Generalized Policy Generation.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Fully Persistent Spatial Data Structures for Efficient Queries in Path-Dependent Motion Planning Applications.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields.
Proceedings of the Conference on Robot Learning, 2022

Learning Neuro-Symbolic Skills for Bilevel Planning.
Proceedings of the Conference on Robot Learning, 2022

Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators.
Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, 2022

Discovering State and Action Abstractions for Generalized Task and Motion Planning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
A Sufficient Statistic for Influence in Structured Multiagent Environments.
J. Artif. Intell. Res., 2021

Learning compositional models of robot skills for task and motion planning.
Int. J. Robotics Res., 2021

Specifying and achieving goals in open uncertain robot-manipulation domains.
CoRR, 2021

Integrated Task and Motion Planning.
Annu. Rev. Control. Robotics Auton. Syst., 2021

Active Learning of Abstract Plan Feasibility.
Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning When to Quit: Meta-Reasoning for Motion Planning.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Learning Symbolic Operators for Task and Motion Planning.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Temporal and Object Quantification Networks.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Shape-Based Transfer of Generic Skills.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

A large-scale benchmark for few-shot program induction and synthesis.
Proceedings of the 38th International Conference on Machine Learning, 2021

Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Learning Online Data Association.
CoRR, 2020

Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time.
CoRR, 2020

GLIB: Exploration via Goal-Literal Babbling for Lifted Operator Learning.
CoRR, 2020

Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Visual Prediction of Priors for Articulated Object Interaction.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Online Replanning in Belief Space for Partially Observable Task and Motion Problems.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Meta-learning curiosity algorithms.
Proceedings of the 8th International Conference on Learning Representations, 2020

CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs.
Proceedings of the 4th Conference on Robot Learning, 2020

Elimination of All Bad Local Minima in Deep Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning.
Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling, 2020

Few-Shot Bayesian Imitation Learning with Logical Program Policies.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Every Local Minimum Value Is the Global Minimum Value of Induced Model in Nonconvex Machine Learning.
Neural Comput., 2019

Effect of Depth and Width on Local Minima in Deep Learning.
Neural Comput., 2019

Modeling and Planning with Macro-Actions in Decentralized POMDPs.
J. Artif. Intell. Res., 2019

Learning to guide task and motion planning using score-space representation.
Int. J. Robotics Res., 2019

Few-Shot Bayesian Imitation Learning with Logic over Programs.
CoRR, 2019

Every Local Minimum is a Global Minimum of an Induced Model.
CoRR, 2019

Differentiable Algorithm Networks for Composable Robot Learning.
Proceedings of the Robotics: Science and Systems XV, 2019

Neural Relational Inference with Fast Modular Meta-learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Learning Quickly to Plan Quickly Using Modular Meta-Learning.
Proceedings of the International Conference on Robotics and Automation, 2019

Combining Physical Simulators and Object-Based Networks for Control.
Proceedings of the International Conference on Robotics and Automation, 2019

Graph Element Networks: adaptive, structured computation and memory.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning sparse relational transition models.
Proceedings of the 7th International Conference on Learning Representations, 2019

Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
From Skills to Symbols: Learning Symbolic Representations for Abstract High-Level Planning.
J. Artif. Intell. Res., 2018

Sampling-based methods for factored task and motion planning.
Int. J. Robotics Res., 2018

FFRob: Leveraging symbolic planning for efficient task and motion planning.
Int. J. Robotics Res., 2018

Provably safe robot navigation with obstacle uncertainty.
Int. J. Robotics Res., 2018

Modular meta-learning in abstract graph networks for combinatorial generalization.
CoRR, 2018

Residual Policy Learning.
CoRR, 2018

Learning sparse relational transition models.
CoRR, 2018

Planning to Give Information in Partially Observed Domains with a Learned Weighted Entropy Model.
CoRR, 2018

STRIPStream: Integrating Symbolic Planners and Blackbox Samplers.
CoRR, 2018

Look Before You Sweep: Visibility-Aware Motion Planning.
Proceedings of the Algorithmic Foundations of Robotics XIII, 2018

Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Active Model Learning and Diverse Action Sampling for Task and Motion Planning.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Integrating Human-Provided Information into Belief State Representation Using Dynamic Factorization.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Finding Frequent Entities in Continuous Data.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Reliably Arranging Objects in Uncertain Domains.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Selecting Representative Examples for Program Synthesis.
Proceedings of the 35th International Conference on Machine Learning, 2018

Adaptable replanning with compressed linear action models for learning from demonstrations.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Learning What Information to Give in Partially Observed Domains.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Modular meta-learning.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Guiding Search in Continuous State-Action Spaces by Learning an Action Sampler From Off-Target Search Experience.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Learning to select examples for program synthesis.
CoRR, 2017

Guiding the search in continuous state-action spaces by learning an action sampling distribution from off-target samples.
CoRR, 2017

Generalization in Deep Learning.
CoRR, 2017

STRIPS Planning in Infinite Domains.
CoRR, 2017

Learning to Acquire Information.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Intelligent Robots in an Uncertain World.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Sample-Based Methods for Factored Task and Motion Planning.
Proceedings of the Robotics: Science and Systems XIII, 2017

Focused model-learning and planning for non-Gaussian continuous state-action systems.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Learning to guide task and motion planning using score-space representation.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Learning composable models of parameterized skills.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

2016
Policy search for multi-robot coordination under uncertainty.
Int. J. Robotics Res., 2016

Decidability of Semi-Holonomic Prehensile Task and Motion Planning.
Proceedings of the Algorithmic Foundations of Robotics XII, 2016

Object-Based World Modeling in Semi-Static Environments with Dependent Dirichlet Process Mixtures.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Learning to Rank for Synthesizing Planning Heuristics.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Searching for physical objects in partially known environments.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Implicit belief-space pre-images for hierarchical planning and execution.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2015
Data association for semantic world modeling from partial views.
Int. J. Robotics Res., 2015

Bayesian Optimization with Exponential Convergence.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Generalizing Over Uncertain Dynamics for Online Trajectory Generation.
Proceedings of the Robotics Research, 2015

Hierarchical planning for multi-contact non-prehensile manipulation.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Backward-forward search for manipulation planning.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Symbol Acquisition for Probabilistic High-Level Planning.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Planning for decentralized control of multiple robots under uncertainty.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Probabilistic Planning for Decentralized Multi-Robot Systems.
Proceedings of the 2015 AAAI Fall Symposia, Arlington, Virginia, USA, November 12-14, 2015, 2015

2014
FFRob: An Efficient Heuristic for Task and Motion Planning.
Proceedings of the Algorithmic Foundations of Robotics XI, 2014

A constraint-based method for solving sequential manipulation planning problems.
Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014

Not seeing is also believing: Combining object and metric spatial information.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Tracking the spin on a ping pong ball with the quaternion Bingham filter.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Interactive Bayesian identification of kinematic mechanisms.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Planning with macro-actions in decentralized POMDPs.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

Constructing Symbolic Representations for High-Level Planning.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

Optimizing a Start-Stop Controller Using Policy Search.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Integrated task and motion planning in belief space.
Int. J. Robotics Res., 2013

Foresight and reconsideration in hierarchical planning and execution.
Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013

Manipulation-based active search for occluded objects.
Proceedings of the 2013 IEEE International Conference on Robotics and Automation, 2013

Object placement as inverse motion planning.
Proceedings of the 2013 IEEE International Conference on Robotics and Automation, 2013

Optimization in the now: Dynamic peephole optimization for hierarchical planning.
Proceedings of the 2013 IEEE International Conference on Robotics and Automation, 2013

A hierarchical approach to manipulation with diverse actions.
Proceedings of the 2013 IEEE International Conference on Robotics and Automation, 2013

Symbol Acquisition for Task-Level Planning.
Proceedings of the Learning Rich Representations from Low-Level Sensors, 2013

2012
Manipulation with Multiple Action Types.
Proceedings of the Experimental Robotics, 2012

Collision-free state estimation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2012

Non-Gaussian belief space planning: Correctness and complexity.
Proceedings of the IEEE International Conference on Robotics and Automation, 2012

LQR-RRT*: Optimal sampling-based motion planning with automatically derived extension heuristics.
Proceedings of the IEEE International Conference on Robotics and Automation, 2012

Unifying perception, estimation and action for mobile manipulation via belief space planning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2012

POMCoP: Belief Space Planning for Sidekicks in Cooperative Games.
Proceedings of the Eighth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2012

Heuristic search of multiagent influence space.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, 2012

Influence-Based Abstraction for Multiagent Systems.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
Robust grasping under object pose uncertainty.
Auton. Robots, 2011

Efficient Planning in Non-Gaussian Belief Spaces and Its Application to Robot Grasping.
Proceedings of the Robotics Research, 2011

Pre-image Backchaining in Belief Space for Mobile Manipulation.
Proceedings of the Robotics Research, 2011

Bayesian Policy Search with Policy Priors.
Proceedings of the IJCAI 2011, 2011

DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes.
Proceedings of the IJCAI 2011, 2011

Hierarchical task and motion planning in the now.
Proceedings of the IEEE International Conference on Robotics and Automation, 2011

CAPIR: Collaborative Action Planning with Intention Recognition.
Proceedings of the Seventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2011

2010
Technical perspective - New bar set for intelligent vehicles.
Commun. ACM, 2010

Planning in partially-observable switching-mode continuous domains.
Ann. Math. Artif. Intell., 2010

Reports of the AAAI 2010 Conference Workshops.
AI Mag., 2010

Belief space planning assuming maximum likelihood observations.
Proceedings of the Robotics: Science and Systems VI, 2010

Task-Driven Tactile Exploration.
Proceedings of the Robotics: Science and Systems VI, 2010

Intelligent Interaction with the Real World.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Class-specific grasping of 3D objects from a single 2D image.
Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

Hierarchical Planning in the Now.
Proceedings of the Bridging the Gap Between Task and Motion Planning, 2010

2009
Segmentation According to Natural Examples: Learning Static Segmentation from Motion Segmentation.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Learning to generate novel views of objects for class recognition.
Comput. Vis. Image Underst., 2009

2008
Automated Design of Adaptive Controllers for Modular Robots using Reinforcement Learning.
Int. J. Robotics Res., 2008

Multi-Agent Filtering with Infinitely Nested Beliefs.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Continuous-State POMDPs with Hybrid Dynamics.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2008

Efficient Distributed Reinforcement Learning through Agreement.
Proceedings of the Distributed Autonomous Robotic Systems 8, 2008

Learning Grammatical Models for Object Recognition.
Proceedings of the Logic and Probability for Scene Interpretation, 24.02. - 29.02.2008, 2008

Lifted Probabilistic Inference with Counting Formulas.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Learning Symbolic Models of Stochastic Domains.
J. Artif. Intell. Res., 2007

Predicting Partial Paths from Planning Problem Parameters.
Proceedings of the Robotics: Science and Systems III, 2007

Efficient Bayesian Task-Level Transfer Learning.
Proceedings of the IJCAI 2007, 2007

Grasping POMDPs.
Proceedings of the 2007 IEEE International Conference on Robotics and Automation, 2007

Logical Particle Filtering.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

Learning Probabilistic Relational Dynamics for Multiple Tasks.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

Virtual Training for Multi-View Object Class Recognition.
Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

Action-Space Partitioning for Planning.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2005
Hedged learning: regret-minimization with learning experts.
Proceedings of the Machine Learning, 2005

Learning Planning Rules in Noisy Stochastic Worlds.
Proceedings of the Proceedings, 2005

Learning Static Object Segmentation from Motion Segmentation.
Proceedings of the Proceedings, 2005

2004
Learning Probabilistic Relational Planning Rules.
Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Ninth International Conference (KR2004), 2004

Learning distributed control for modular robots.
Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan, September 28, 2004

Representing Hierarchical POMDPs as DBNs for Multi-scale Robot Localization.
Proceedings of the 2004 IEEE International Conference on Robotics and Automation, 2004

Mobilized Ad-Hoc Networks: A Reinforcement Learning Approach.
Proceedings of the 1st International Conference on Autonomic Computing (ICAC 2004), 2004

Multi-Agent Learning in Mobilized Ad-Hoc Networks.
Proceedings of the Artificial Multiagent Learning, 2004

2003
A Dynamical Model of Visually-Guided Steering, Obstacle Avoidance, and Route Selection.
Int. J. Comput. Vis., 2003

Approximate Planning in POMDPs with Macro-Actions.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Envelope-based Planning in Relational MDPs.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

All learning is Local: Multi-agent Learning in Global Reward Games.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2002
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap.
J. Artif. Intell. Res., 2002

The Thing that we Tried Didn't Work very Well: Deictic Representation in Reinforcement Learning.
Proceedings of the UAI '02, 2002

Effective Reinforcement Learning for Mobile Robots.
Proceedings of the 2002 IEEE International Conference on Robotics and Automation, 2002

Nearly Deterministic Abstractions of Markov Decision Processes.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001
Playing is believing: The role of beliefs in multi-agent learning.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Holonomic planar motion from non-holonomic driving mechanisms: the front-point method.
Proceedings of the Mobile Robots XVI, Boston, 2001

Reinforcement learning for robot control.
Proceedings of the Mobile Robots XVI, Boston, 2001

Approaches to macro decompositions of large Markov decision process planning problems.
Proceedings of the Mobile Robots XVI, Boston, 2001

2000
Learning to Cooperate via Policy Search.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Adaptive Importance Sampling for Estimation in Structured Domains.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Practical Reinforcement Learning in Continuous Spaces.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

State-based Classification of Finger Gestures from Electromyographic Signals.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

Sampling Methods for Action Selection in Influence Diagrams.
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

1999
Accelerating EM: An Empirical Study.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Learning Finite-State Controllers for Partially Observable Environments.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Solving POMDPs by Searching the Space of Finite Policies.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs.
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

Learning Policies with External Memory.
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999

1998
Planning and Acting in Partially Observable Stochastic Domains.
Artif. Intell., 1998

Ecological Robotics.
Adapt. Behav., 1998

Hierarchical Solution of Markov Decision Processes using Macro-actions.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Heading in the Right Direction.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

A Framework for Reinforcement Learning on Real Robots.
Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

Solving Very Large Weakly Coupled Markov Decision Processes.
Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

1997
Learning Topological Maps with Weak Local Odometric Information.
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

1996
Introduction.
Mach. Learn., 1996

Reinforcement Learning: A Survey.
J. Artif. Intell. Res., 1996

The National Science Foundation Workshop on Reinforcement Learning.
AI Mag., 1996

On reinforcement learning for robots.
Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS 1996, 1996

Acting under uncertainty: discrete Bayesian models for mobile-robot navigation.
Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS 1996, 1996

1995
Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning.
Mach. Learn., 1995

A Situated View of Representation and Control.
Artif. Intell., 1995

Planning under Time Constraints in Stochastic Domains.
Artif. Intell., 1995

Learning Dynamics: System Identification for Perceptually Challenged Agents.
Artif. Intell., 1995

On the Complexity of Solving Markov Decision Problems.
Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

Partially Observable Markov Decision Processes for Artificial Intelligence.
Proceedings of the KI-95: Advances in Artificial Intelligence, 1995

Learning Policies for Partially Observable Environments: Scaling Up.
Proceedings of the Machine Learning, 1995

1994
Associative Reinforcement Learning: A Generate and Test Algorithm.
Mach. Learn., 1994

Associative Reinforcement Learning: Functions in k-DNF.
Mach. Learn., 1994

Learning and intelligent Agents.
Proceedings of the Eleventh European Conference on Artificial Intelligence, 1994

Acting Optimally in Partially Observable Stochastic Domains.
Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994

1993
Deliberation Scheduling for Time-Critical Sequential Decision Making.
Proceedings of the UAI '93: Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence, 1993

Learning to Achieve Goals.
Proceedings of the 13th International Joint Conference on Artificial Intelligence. Chambéry, France, August 28, 1993

Hierarchical Learning in Stochastic Domains: Preliminary Results.
Proceedings of the Machine Learning, 1993

Planning With Deadlines in Stochastic Domains.
Proceedings of the 11th National Conference on Artificial Intelligence. Washington, 1993

Learning in embedded systems.
MIT Press, ISBN: 978-0-262-11174-4, 1993

1991
A Situated-Automata Approach to the Design of Embedded Agents.
SIGART Bull., 1991

Foundations of learning in autonomous agents.
Robotics Auton. Syst., 1991

Input Generalization in Delayed Reinforcement Learning: An Algorithm and Performance Comparisons.
Proceedings of the 12th International Joint Conference on Artificial Intelligence. Sydney, 1991

1990
Learning in embedded systems.
PhD thesis, 1990

Action and planning in embedded agents.
Robotics Auton. Syst., 1990

Learning Functions in k-DNF from Reinforcement.
Proceedings of the Machine Learning, 1990

1989
Intelligent Robots in the Real World.
Proceedings of the Information Processing 89, Proceedings of the IFIP 11th World Computer Congress, San Francisco, USA, August 28, 1989

A Formal Framework for Learning in Embedded Systems.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

1988
Artificial Intelligence and Robotics.
Proceedings of the COMPCON'88, Digest of Papers, Thirty-Third IEEE Computer Society International Conference, San Francisco, California, USA, February 29, 1988

Goals as Parallel Program Specifications.
Proceedings of the 7th National Conference on Artificial Intelligence, 1988

1986
The Synthesis of Digital Machines With Provable Epistemic Properties.
Proceedings of the 1st Conference on Theoretical Aspects of Reasoning about Knowledge, 1986


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