- Ecological Robotics: Controlling Behavior with Optical Flow Andrew P. Duchon William H. Warren Leslie Pack Kaelbling
- Learning to Achieve Goals Leslie Pack Kaelbling \Lambda
- Representing hierarchical POMDPs as DBNs for multi-scale robot localization
- Learning Static Object Segmentation from Motion Segmentation Michael G. Ross and Leslie Pack Kaelbling
- Segmentation According to Natural Examples: Learning Static Segmentation from Motion Segmentation (pre-print)
- Playing is believing: The role of beliefs in multi-agent learning
- On the Complexity of Solving Markov Decision Problems Michael L. Littman, Thomas L. Dean, Leslie Pack Kaelbling
- Shortest Paths in a Dynamic Uncertain Domain David Meir Blei
- Sampling Methods for Action Selection in Influence Diagrams Luis E. Ortiz
- Solving POMDPs by Searching the Space of Finite Policies Nicolas Meuleau, KeeEung Kim, Leslie Pack Kaelbling and Anthony R. Cassandra
- Adaptive Importance Sampling for Estimation in Structured Domains Luis E. Ortiz
- Learning Dynamics: System Identification for Perceptually Challenged Agents
- Hierarchical Task and Motion Planning in the Now Leslie Pack Kaelbling and Tomas Lozano-Perez
- A Systematic Approach to Learning Object Segmentation from Motion
- Planning Under Time Constraints in Stochastic Domains Thomas Dean, Leslie Pack Kaelbling, Jak Kirman, Ann Nicholson
- Statebased Classification of Finger Gestures from Electromyographic Signals Peter Ju PJU@MIT.EDU
- Efficient Bayesian Task-Level Transfer Learning Daniel M. Roy and Leslie P. Kaelbling
- Ecological Robotics Andrew P. Duchon
- Learning to Cooperate via Policy Search Leonid Peshkin
- A Situated View of Representation and Control Stanley J. Rosenschein \Lambda
- Small Journal Name, ??, 1--20 (??) fl ?? Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Learning Object Segmentation from Video Data
- Efficient Distributed Reinforcement Learning Through Agreement
- Toward Hierachical Decomposition for Planning in Uncertain Environments Terran Lane and Leslie Pack Kaelbling
- Journal of Artificial Intelligence Research 4 (1996) 237285 Submitted 9/95; published 5/96 Reinforcement Learning: A Survey
- Learning Policies with External Memory Leonid Peshkin
- Accelerating EM: An Empirical Study Luis E. Ortiz and Leslie Pack Kaelbling y
- Learning Probabilistic Relational Planning Rules Hanna M. Pasula
- Learning policies for partially observable environments: Scaling up Michael L. Littman
- Ann Math Artif Intell DOI 10.1007/s10472-010-9202-1
- Task-Driven Tactile Exploration Kaijen Hsiao
- Belief space planning assuming maximum likelihood observations
- Learning to generate novel views of objects for class recognition Han-Pang Chiu *, Leslie Pack Kaelbling, Toms Lozano-Prez
- Automated Design of Adaptive Controllers for Modular Robots using Reinforcement Learning
- Action-Space Partitioning for Planning Natalia H. Gardiol, Leslie Pack Kaelbling
- Approximate Planning in POMDPs with Macro-Actions
- Envelope-based Planning in Relational MDPs Natalia H. Gardiol
- Learning Distributed Control for Modular Robots Paulina Varshavskaya, Leslie Pack Kaelbling and Daniela Rus
- Representing hierarchical POMDPs as DBNs for multi-scale robot localization
- Effective Reinforcement Learning for Mobile Robots
- Learning with Deictic Representation
- Nearly Deterministic Abstractions of Markov Decision Processes Terran Lane and Leslie Pack Kaelbling
- Artificial Intelligence 101 (1998) 99134 Planning and acting in partially observable
- Robust Belief-Based Execution of Manipulation Programs
- Mobilized ad-hoc networks: A reinforcement learning approach
- Acting under Uncertainty: Discrete Bayesian Models for MobileRobot Navigation
- Logical Particle Filtering Luke S. Zettlemoyer, Hanna M. Pasula, and Leslie Pack Kaelbling
- Lifted Probabilistic Inference with Counting Formulas Brian Milch, Luke S. Zettlemoyer, Kristian Kersting, Michael Haimes, Leslie Pack Kaelbling
- Small Journal Name, ??, 1--20 (??) fl ?? Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- Learning Topological Maps with Weak Local Odometric Information Hagit Shatkay Leslie Pack Kaelbling
- Heading in the Right Direction Hagit Shatkay Leslie P. Kaelbling
- Practical Reinforcement Learning in Continuous Spaces William D. Smart wds@cs.brown.edu
- Learning FiniteState Controllers for Partially Observable Environments Nicolas Meuleau, Leonid Peshkin, KeeEung Kim and Leslie Pack Kaelbling
- Learning Planning Rules in Noisy Stochastic Worlds Luke S. Zettlemoyer
- Combining dynamic abstractions in very large MDPs Kurt Steinkraus, Leslie Pack Kaelbling
- Hierarchical Learning in Stochastic Domains: Preliminary Results Leslie Pack Kaelbling
- Collision Avoidance for Unmanned Aircraft using Markov Decision Processes
- Hierarchical Solution of Large Markov Decision Processes Jennifer Barry and Leslie Pack Kaelbling and Tomas Lozano-Perez
- Predicting Partial Paths from Planning Problem Sarah Finney, Leslie Kaelbling, Tomas Lozano-Perez
- Journal of Artificial Intelligence Research 1 (2005) Submitted 10/05; published 01/06 Learning Symbolic Models of Stochastic Domains
- Acting Optimally in Partially Observable Stochastic Domains Anthony R. Cassandra \Lambda , Leslie Pack Kaelbling y
- Learning Probabilistic Relational Dynamics for Multiple Tasks Ashwin Deshpande
- Efficient planning in non-Gaussian belief spaces and its application to robot grasping
- Domain and Plan Representation for Task and Motion Planning in Uncertain Domains
- Computer Science and Artificial Intelligence Laboratory Technical Report
- Pre-image backchaining in belief space for mobile manipulation
