Background Image

Publications

A full list of publications in reverse chronological order, across all areas.

2020

[265] Meta-learning curiosity algorithms (Alet, Ferran and Schneider, Martin and Lozano-Perez, Tomas and Kaelbling, Leslie Pack), In International Conference on Learning Representations (ICLR), 2020. BIBTEXPDF
[264] PDDLStream: Integrating Symbolic Planners and Blackbox Samplers (Garrett, Caelan R. and Lozano-Perez, Tomas and Kaelbling, Leslie P.), In International Conference on Automated Planning and Scheduling (ICAPS), 2020. BIBTEXPDF
[263] Online Replanning in Belief Space for Partially Observable Task and Motion Problems (Garrett, Caelan R. and Paxton, Chris and Lozano-Perez, Tomas and Kaelbling, Leslie P. and Fox, Dieter), In International Conference on Robotics and Automation (ICRA), 2020. BIBTEXPDF
[262] Adaptive Activation Functions Accelerate Convergence in Deep and Physics-informed Neural Networks (Ameya D. Jagtap, Kenji Kawaguchi and George E. Karniadakis), In Journal of Computational Physics, volume 404, 2020. BIBTEXPDF
[261] Elimination of All Bad Local Minima in Deep Learning (Kenji Kawaguchi and Leslie Pack Kaelbling), In 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 2020. BIBTEXPDF
[260] Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization (Kenji Kawaguchi and Haihao Lu), In 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 2020. BIBTEXPDF
[259] Monte Carlo Tree Search in continuous spaces using Voronoi optimistic optimization with regret bounds (Beomjoon Kim, Kyungjae Lee, Sungbin Lim, Leslie Pack Kaelbling, Tomas Lozano-Perez), In AAAI Conference on Artificial Intelligence (AAAI), 2020. BIBTEXPDF
[258] Few-shot Bayesian Imitation Learning with Logical Program Policies (Silver, Tom and Allen, Kelsey R. and Lew, Alex K. and Kaelbling, Leslie Pack and Tenenbaum, Josh), In AAAI Conference on Artificial Intelligence (AAAI), 2020. BIBTEXPDF

2019

[257] Learning to guide task and motion planning using score-space representation (Beomjoon Kim, Zi Wang, Leslie Pack Kaelbling, Tomas Lozano-Perez), In International Journal of Robotics Research, 2019. BIBTEXPDF
[256] Graph Element Networks: adaptive, structured computation and memory (Alet, Ferran and Jeewajee, Adarsh Keshav and Villalonga, Maria Bauza and Rodriguez, Alberto and Lozano-Perez, Tomas and Kaelbling, Leslie), In Proceedings of the 36th International Conference on Machine Learning, volume 97, 2019. BIBTEXPDF
[255] Modeling and Planning with Macro-Actions in Decentralized POMDPs (Christopher Amato and George Konidaris and Leslie Pack Kaelbling and Jonathan P. How), In Journal of Artificial Intelligence Research, volume 64, 2019. BIBTEXPDF
[254] Effect of Depth and Width on Local Minima in Deep Learning (Kenji Kawaguchi, Jiaoyang Huang and Leslie Pack Kaelbling), In Neural Computation, volume 31, 2019. BIBTEXPDF
[253] Depth with Nonlinearity Creates No Bad Local Minima in ResNets (Kenji Kawaguchi and Yoshua Bengio), In Neural Networks, volume 118, 2019. BIBTEXPDF
[252] Learning sparse relational transition models (Victoria Xia and Zi Wang and Kelsey Allen and Tom Silver and Leslie Pack Kaelbling), In International Conference on Learning Representations (ICLR), 2019. BIBTEXPDF
[251] Adversarial actor-critic method for task and motion planning problems using planning experience (Beomjoon Kim and Leslie Pack Kaelbling and Tomas Lozano-Perez), In AAAI Conference on Artificial Intelligence (AAAI), 2019. BIBTEXPDF
[250] Learning Quickly to Plan Quickly Using Modular Meta-Learning (Rohan Chitnis and Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Conference on Robotics and Automation (ICRA), 2019. BIBTEXPDF
[249] Differentiable Algorithm Networks for Composable Robot Learning (Peter Karkus and Xiao Ma and David Hsu and Leslie Pack Kaelbling and Wee Sun Lee and Tomas Lozano-Perez), In Robotics: Science and Systems (RSS), 2019. BIBTEXPDF
[248] Learning Compact Models for Planning with Exogenous Processes (Rohan Chitnis and Tomas Lozano-Perez), In Conference on Robot Learning, 2019. BIBTEXPDF
[247] Learning value functions with relational state representations for guiding task-and-motion planning (Beomjoon Kim, Luke Shimanuki), In Conference on Robot Learning, 2019. BIBTEXPDF
[246] A Lagrangian Method for Inverse Problems in Reinforcement Learning (Pierre-Luc Bacon, Florian Schaefer, Clement Gehring, Animashree Anandkumar, Emma Brunskill), In NeurIPS Optimization Foundations for Reinforcement Learning Workshop, 2019. BIBTEXPDF
[245] Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video (Maria Bauza and Ferran Alet and Yen-Chen Lin and Tomas Lozano-Perez and Leslie P. Kaelbling and Phillip Isola and Alberto Rodriguez), In International Conference on Intelligent Robots and Systems (IROS), 2019. BIBTEXPDF
[244] Force-And-Motion Constrained Planning for Tool Use (Rachel Holladay and Tomas Lozano-Perez and Alberto Rodriguez), In International Conference on Intelligent Robots and Systems (IROS), 2019. BIBTEXPDF
[243] Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes (Kenji Kawaguchi and Jiaoyang Huang), In 57th Allerton Conference on Communication, Control, and Computing (Allerton), 2019. BIBTEXPDF
[242] Every Local Minimum Value is the Global Minimum Value of Induced Model in Non-convex Machine Learning (Kenji Kawaguchi, Jiaoyang Huang and Leslie Pack Kaelbling), In Neural Computation, volume 31, 2019. BIBTEXPDF
[241] Neural Relational Inference with Fast Modular Meta-learning (Alet, Ferran and Weng, Erica and Lozano-Perez, Tomas and Kaelbling, Leslie Pack), , 2019. BIBTEXPDF

2018

[240] Automated sequence and motion planning for robotic spatial extrusion of 3D trusses (Huang, Yijiangand Garrett, Caelan R.and Mueller, Caitlin T.), In Construction Robotics, volume 2, 2018. BIBTEXPDF
[239] Look before you sweep: Visibility-aware motion planning (Gustavo Goretkin and Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018. BIBTEXPDF
[238] Hardness of 3D Motion Planning Under Obstacle Uncertainty (Luke Shimanuki and Brian Axelrod), In International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018. BIBTEXPDF
[237] Sampling-based methods for factored task and motion planning (Caelan Reed Garrett, Tomas Lozano-Perez, Leslie Pack Kaelbling), In The International Journal of Robotics Research, 2018. BIBTEXPDF
[236] Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior (Zi Wang and Beomjoon Kim and Leslie Pack Kaelbling), In Neural Information Processing Systems (NeurIPS), 2018. BIBTEXPDF
[235] Adaptable replanning with compressed linear action models for learning from demonstrations (Clement Gehring, Leslie Pack Kaelbling, Tomas Lozano-Perez), In Conference on Robot Learning (CoRL), 2018. BIBTEXPDF
[234] Modular meta-learning (Ferran Alet, Tomas Lozano-Perez, Leslie Pack Kaelbling), In Conference on Robot Learning (CoRL), 2018. BIBTEXPDF
[233] Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing (Anurag Ajay, Jiajun Wu, Nima Fazeli, Maria Bauza, Leslie Pack Kaelbling, Joshua B. Tenenbaum and Alberto Rodriguez), In International Conference on Intelligent Robots and Systems (IROS), 2018. BIBTEXPDF
[232] Active model learning and diverse action sampling for task and motion planning (Zi Wang and Caelan Reed Garrett and Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Conference on Intelligent Robots and Systems (IROS), 2018. BIBTEXPDF
[231] Provably Safe Robot Navigation with Obstacle Uncertainty (Brian Axelrod and Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Journal of Robotics Research, 2018. BIBTEXPDF
[230] Integrating Human-Provided Information Into Belief State Representation Using Dynamic Factorization (Rohan Chitnis and Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Conference on Intelligent Robots and Systems (IROS), 2018. BIBTEXPDF
[229] Robot Juggling (Anders, Ariel), In EAAI-18: The 8th Symposium on Educational Advances in Artificial Intelligence, 2018. BIBTEXPDF
[228] Learning What Information to Give in Partially Observed Domains (Rohan Chitnis and Leslie Pack Kaelbling and Tomas Lozano-Perez), In Conference on Robot Learning (CoRL), 2018. BIBTEXPDF
[227] Generalization in Deep Learning (Kenji Kawaguchi, Leslie Pack Kaelbling, and Yoshua Bengio), In Mathematics of Deep Learning, Cambridge University Press, to appear. Prepint avaliable as: MIT-CSAIL-TR-2018-014, Massachusetts Institute of Technology, 2018. BIBTEXPDF
[226] From Skills to Symbols: Learning Symbolic Representations for Abstract High-Level Planning (Konidaris, George and Kaelbling, Leslie Pack and Lozano-Perez, Tomas), In Journal of Artificial Intelligence Research, volume 61, 2018. BIBTEXPDF
[225] Guiding Search in Continuous State-action Spaces by Learning an Action Sampler from Off-target Search Experience (Beomjoon Kim, Leslie Pack Kaelbling, Tomas Lozano-Perez), In Proceedings of the 32th AAAI Conference on Artificial Intelligence (AAAI). To appear, 2018. BIBTEXPDF
[224] Deep Semi-Random Features for Nonlinear Function Approximation (Kenji Kawaguchi, Bo Xie and Le Song), In Proceedings of the 32th AAAI Conference on Artificial Intelligence (AAAI), 2018. BIBTEXPDF
[223] Reliably arranging objects in uncertain domains (Ariel S. Anders and Leslie P. Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2018. BIBTEXPDF
[222] Batched Large-scale Bayesian Optimization in High-dimensional Spaces (Zi Wang, Clement Gehring, Pushmeet Kohli, Stefanie Jegelka), In International Conference on Artificial Intelligence and Statistics (AISTATS), 2018. BIBTEXPDF

2017

[221] Policy search for multi-robot coordination under uncertainty (Christopher Amato and George Konidaris and Ariel Anders and Gabriel Cruz and Jonathan P How and Leslie P Kaelbling), In The International Journal of Robotics Research, volume 35, 2017. BIBTEXPDF
[220] Visual Servoing (Anders, Ariel and Karaman, Sertac), In EAAI-17: The 7th Symposium on Educational Advances in Artificial Intelligence, 2017. BIBTEXPDF
[219] Electrowetting-on-dielectric Actuation of a Spatial and Angular Manipulation Mems Stage (Daniel J. Preston, Ariel Anders, Banafsheh Barabadi, Evelyn Tio, Yangying Zhu, DingRan Annie Dai, Evelyn N. Wang), In The 30th IEEE International Conference on Micro Electro Mechanical Systems (MEMS 2017), 2017. BIBTEXPDF
[218] FFRob: Leveraging symbolic planning for efficient task and motion planning (Caelan Reed Garrett, Tomas Lozano-Perez, Leslie Pack Kaelbling), In The International Journal of Robotics Research, 2017. BIBTEXPDF
[217] Project-based, Collaborative, Algorithmic Robotics for High SchoolStudents: Programming Self-driving Race Cars at MIT (Sertac Karaman and Ariel Anders and Michael Boulet and Jane Connor andKenneth Gregson and Winter J Guerra and Owen Guldner and Mubarik Mohamoudand Brian Plancher and Robert Shin and John Vivilecchia), In 2017 IEEE Integrated STEM Education Conference (ISEC) (ISEC'17), 2017. BIBTEXPDF
[216] Focused Model-Learning and Planning for Non-Gaussian Continuous State-Action Systems (Zi Wang, Stefanie Jegelka, Leslie Pack Kaelbling, Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2017. BIBTEXPDF
[215] Max-value Entropy Search for Efficient Bayesian Optimization (Zi Wang and Stefanie Jegelka), In International Conference on Machine Learning (ICML), 2017. BIBTEXPDF
[214] Batched High-dimensional Bayesian Optimization via Structural Kernel Learning (Zi Wang, Chengtao Li, Stefanie Jegelka, Pushmeet Kohli), In International Conference on Machine Learning (ICML), 2017. BIBTEXPDF
[213] Learning to guide task and motion planning using score-space representation (Beomjoon Kim, Leslie Pack Kaelbling, Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2017. BIBTEXPDF
[212] Learning composable models of parameterized skills (Leslie Pack Kaelbling, Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2017. BIBTEXPDF
[211] Planning Robust Strategies for Constructing Multi-object Arrangements (Anders, Ariel and Kaelbling, Leslie and Lozano-Perez, Tomas), CSAIL MIT, 2017. BIBTEXPDF
[210] Sample-Based Methods for Factored Task and Motion Planning (Caelan Reed Garrett and Tomas Lozano-Perez and Leslie Pack Kaelbling), In Robotics: Science and Systems (RSS), 2017. BIBTEXPDF
[209] Provably Safe Robot Navigation with Obstacle Uncertainty (Brian Axelrod and Leslie Pack Kaelbling and Tomas Lozano-Perez), In Robotics: Science and Systems (RSS), 2017. BIBTEXPDF

2016

[208] Implicit Belief-Space Pre-images for Hierarchical Planning and Execution (Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2016. BIBTEXPDF
[207] Searching for Physical Objects in Partially Known Environments (Xinkun Nie and Lawson L.S. Wong and Leslie Pack Kaelbling), In IEEE Conference on Robotics and Automation (ICRA), 2016. BIBTEXPDF
[206] Object-based World Modeling in Semi-Static Envrionments with Dependent Dirichlet Process Mixtures (Lawson L.S. Wong and Thanard Kurutach and Tomas Lozano-Perez and Leslie Pack Kaelbling), In International Joint Conference on Artificial Intelligence (IJCAI), 2016. BIBTEXPDF
[205] Learning to Rank for Synthesizing Planning Heuristics (Caelan Reed Garrett and Leslie Pack Kaelbling and Tomas Lozano-Perez), In Int. Joint Conf. on Artificial Intelligence (IJCAI), 2016. BIBTEXPDF
[204] Electrowetting-on-dielectric actuation of a vertical translation and angular manipulation stage (Daniel J. Preston and Ariel Anders and Banafsheh Barabadi and Evelyn Tio and Yangying Zhu and DingRan Annie Dai and Evelyn N. Wang), In Applied Physics Letters, volume 109, 2016. BIBTEXPDF
[203] Decidability of Semi-Holonomic Prehensile Task and Motion Planning (Ashwin Deshpande, Leslie Pack Kaelbling, Tomas Lozano-Perez), In International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2016. BIBTEXPDF
[202] Humanoid manipulation planning using backward-forward search (Grey, Michael X and Garrett, Caelan R and Liu, C Karen and Ames, Aaron D and Thomaz, Andrea L), In Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, 2016. BIBTEXPDF
[201] Global Continuous Optimization with Error Bound and Fast Convergence (Kenji Kawaguchi, Yu Maruyama and Xiaoyu Zheng), In Journal of Artificial Intelligence Research (JAIR), volume 56, 2016. BIBTEXPDF
[200] Deep Learning without Poor Local Minima (Kenji Kawaguchi), In Advances in Neural Information Processing Systems (NeurIPS), 2016. BIBTEXPDF
[199] Optimization as Estimation with Gaussian Processes in Bandit Settings (Zi Wang, Bolei Zhou, Stefanie Jegelka), In International Conference on Artificial Intelligence and Statistics (AISTATS), 2016. BIBTEXPDF
[198] Bounded Optimal Exploration in MDP (Kenji Kawaguchi), In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), 2016. BIBTEXPDF
[197] Optimization as Estimation with Gaussian Processes in Bandit Settings (Zi Wang, Bolei Zhou, Stefanie Jegelka), In International Conference on Artificial Intelligence and Statistics (AISTATS), 2016. BIBTEXPDF
[196] Bounded Optimal Exploration in MDP (Kenji Kawaguchi), In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), 2016. BIBTEXPDF

2015

[195] Data association for semantic world modeling from partial views (Lawson L.S. Wong and Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Journal of Robotics Research, volume 34, 2015. BIBTEXPDF
[194] Symbol Acquisition for Probabilistic High-Level Planning (G.D. Konidaris and L.P. Kaelbling and T. Lozano-Perez), In Proceedings of the Twenty Fourth International Joint Conference on Artificial Intelligence (IJCAI), 2015. BIBTEXPDF
[193] Policy Search for Multi-Robot Coordination under Uncertainty (C. Amato and G.D. Konidaris and A. Anders and G. Cruz and J.P. How and L.P. Kaelbling), In Robotics: Science and Systems XI (RSS), 2015. BIBTEXPDF
[192] Planning for Decentralized Control of Multiple Robots Under Uncertainty (C. Amato and G.D. Konidaris and G. Cruz and C. Maynor and J.P. How and L.P. Kaelbling), In Proceedings of the 2015 IEEE International Conference on Robotics and Automation, 2015. BIBTEXPDF
[191] Hierarchical planning for multi-contact non-prehensile manipulation (Gilwoo Lee and Tomas Lozano-Perez and Leslie Pack Kaelbling), In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015. BIBTEXPDF
[190] Backward-Forward Search for Manipulation Planning (Caelan Reed Garrett and Tomas Lozano-Perez and Leslie Pack Kaelbling), In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015. BIBTEXPDF
[189] Generalizing over Uncertain Dynamics for Online Trajectory Generation (Beomjoon Kim and Albert Kim and Hongkai Dai and Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Symposium of Robotics Research (ISRR), 2015. BIBTEXPDF
[188] Bayesian optimization with exponential convergence (Kenji Kawaguchi and Leslie Pack Kaelbling and Tomas Lozano-Perez), In Advances in Neural Information Processing Systems (NeurIPS), 2015. BIBTEXPDF

2014

[187] Not Seeing is Also Believing: Combining Object and Metric Spatial Information (Lawson L.S. Wong and Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2014. BIBTEXPDF
[186] Interactive Bayesian Identification of Kinematic Mechanisms (Patrick R. Barragan and Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2014. BIBTEXPDF
[185] Tracking the Spin on a Ping Pong Ball with the Quaternion Bingham Filter (Jared Glover and Leslie Pack Kaelbling), In IEEE Conference on Robotics and Automation (ICRA), 2014. BIBTEXPDF
[184] Exploiting Separability in Multi-Agent Planning with Continuous-State MDPs. (Jilles S. Dibangoye and Christopher Amato and Olivier Buffet and Francois Charpillet), In Thirteenth International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-14), 2014. BIBTEXPDF
[183] Planning with Macro-Actions in Decentralized POMDPs (Christopher Amato and George Konidaris and Leslie Pack Kaelbling), In Thirteenth International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-14), 2014. BIBTEXPDF
[182] Constructing Symbolic Representations for High-Level Planning (George D. Konidaris and Leslie Kaelbling and Tomas Lozano-Perez), In Proceedings of the Twenty-Eighth Conference on Artificial Intelligence, 2014. BIBTEXPDF
[181] A constraint-based method for solving sequential manipulation planning problems (Tomas Lozano-Perez and Leslie Pack Kaelbling), In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014. BIBTEXPDF
[180] FFRob: An efficient heuristic for task and motion planning (Caelan Reed Garrett and Tomas Lozano-Perez and Leslie Pack Kaelbling), In International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2014. BIBTEXPDF
[179] Generalizing Policy Advice with Gaussian Process Bandits for Dynamic Skill Improvement (Jared Glover and Charlotte Zhu), In Proceedings of the Twenty-Eighth Conference on Artificial Intelligence, 2014. BIBTEXPDF
[178] Learning a strategy for whole-arm grasping (Ariel S. Anders), Massachusetts Institute of Technology, 2014. BIBTEXPDF

2013

[177] Optimization in the Now: Dynamic Peephole Optimization for Hierarchical Planning (Dylan Hadfield-Menell and Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2013. BIBTEXPDF
[176] Manipulation-based Active Search for Occluded Objects (Lawson L.S. Wong and Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2013. BIBTEXPDF
[175] Object Placement as Inverse Motion Planning (Anne Holladay and Jennifer Barry and Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2013. BIBTEXPDF
[174] A Hierarchical Approach to Manipulation with Diverse Actions (Jennifer Barry and Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2013. BIBTEXPDF
[173] Integrated Task and Motion Planning in Belief Space (Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Journal of Robotics Research, volume 32, 2013. BIBTEXPDF
[172] Optimal Sampling-Based Planning for Linear-Quadratic Kinodynamic Systems (G. Goretkin and A. Perez and R. Platt and G.D. Konidaris), In IEEE Conference on Robotics and Automation (ICRA), 2013. BIBTEXPDF
[171] Constructing Semantic World Models from Partial Views (Lawson L.S. Wong and Leslie Pack Kaelbling and Tomas Lozano-Perez), In Robotics: Science and Systems (RSS) Workshop on Robots in Clutter, 2013. BIBTEXPDF
[170] Data association for semantic world modeling from partial views (Lawson L.S. Wong and Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Symposium of Robotics Research, 2013. BIBTEXPDF
[169] Foresight and Reconsideration in Hierarchical Planning and Execution (Martin Levihn and Leslie Pack Kaelbling and Tomas Lozano-Perez and Mike Stilman), In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013. BIBTEXPDF
[168] Bingham Procrustean Alignment for Object Detection in Clutter (Jared Glover and Sanja Popovic), In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013. BIBTEXPDF
[167] Automatic Synthesis of Rules for Planning in Belief Space (Leslie Pack Kaelbling), In RSS Workshop on Combined Robot Motion Planning and AI Planning for Practical Applications, 2013. BIBTEXPDF
[166] Optimally Solving Dec-POMDPs as Continuous-State MDPs (Jilles S. Dibangoye and Christopher Amato and Olivier Buffet and Francois Charpillet), In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, 2013. BIBTEXPDF
[165] Incremental Clustering and Expansion for Faster Optimal Planning in Decentralized POMDPs (Frans A. Oliehoek and Matthijs T. J. Spaan and Christopher Amato and Shimon Whiteson), In Journal of Artificial Intelligence Research, volume 46, 2013. BIBTEXPDF
[164] Producing Efficient Error-bounded Solutions for Transition Independent Decentralized MDPs (Jilles S. Dibangoye and Christopher Amato and Arnaud Doniec and Francois Charpillet), In Proceedings of the Twelfth International Conference on Autonomous Agents and Multiagent Systems, 2013. BIBTEXPDF

2012

[163] Heuristic Search of Multiagent Influence Space (Stefan Witwicki andFrans A. Oliehoek and Leslie P. Kaelbling), In Proceedings of The International Joint Conference on Autonomous Agents and Multi Agent Systems, 2012. BIBTEXPDF
[162] Decentralized POMDPs (Frans A. Oliehoek), , volume 12, 2012. BIBTEXPDF
[161] Scaling Up Decentralized MDPs Through Heuristic Search (Jilles S. Dibangoye and Christopher Amato and Arnaud Doniec), In Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012. BIBTEXPDF
[160] Diagnose and Decide: An Optimal Bayesian Approach (Christopher Amato and Emma Brunskill), In Proceedings of the Workshop on Bayesian Optimization and Decision Making at NIPS 2012, 2012. BIBTEXPDF
[159] Transfer Learning by Discovering Latent Task Parametrizations (F. Doshi-Velez and G.D. Konidaris), In NIPS 2012 Workshop on Bayesian Nonparametric Models for Reliable Planning And Decision-Making Under Uncertainty, 2012. BIBTEXPDF
[158] POMCoP: Belief Space Planning for Sidekicks in Cooperative Games (O. Macindoe and L. P. Kaelbling and T. Lozano-Perez), In Proceedings of the 8th Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2012. BIBTEXPDF
[157] Learning and Generalization of Complex Tasks from Unstructured Demonstrations (S. Niekum and S. Osentoski and G.D. Konidaris and A.G. Barto), In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012. BIBTEXPDF
[156] Transfer in Reinforcement Learning via Shared Features (G.D. Konidaris and I. Scheidwasser and A.G. Barto), In Journal of Machine Learning Research, volume 13, 2012. BIBTEXPDF
[155] Learning Parameterized Skills (B.C. da Silva and G.D. Konidaris and A.G. Barto), In Proceedings of the Twenty Ninth International Conference on Machine Learning, 2012. BIBTEXPDF
[154] Manipulation with Multiple Action Types (J. Barry and K. Hsiao and L. P. Kaelbling and T. Lozano-Perez), In International Symposium on Experimental Robotics, 2012. BIBTEXPDF
[153] Robot Learning from Demonstration by Constructing Skill Trees (G.D. Konidaris and S.R. Kuindersma and R.A. Grupen and A.G. Barto), In International Journal of Robotics Research, volume 31, 2012. BIBTEXPDF
[152] LQR-RRT*: Optimal Sampling-Based Motion Planning with Automatically Derived Extension Heuristics (A. Perez and R. Platt and G.D. Konidaris and L.P. Kaelbling and T. Lozano-Perez), In Proceedings of the IEEE International Conference on Robotics and Automation, 2012. BIBTEXPDF
[151] Kinematics of reaching and implications for handedness in rhesus monkey infants (E.L. Nelson and G.D. Konidaris and N.E. Berthier and M.C. Braun and M.S.F.X. Novak and S.J. Suomi and M.A. Novak), In Developmental Psychobiology, volume 54, 2012. BIBTEXPDF
[150] Collision-Free State Estimation (Lawson L.S. Wong and Leslie P. Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2012. BIBTEXPDF
[149] Non-Gaussian Belief Space Planning: Correctness and Complexity (Robert Platt and Leslie Kaelbling and Tomas Lozano-Perez and Russ Tedrake), In IEEE Conference on Robotics and Automation (ICRA), 2012. BIBTEXPDF
[148] Unifying Perception, Estimation and Action for Mobile Manipulation via Belief Space Planning (Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2012. BIBTEXPDF
[147] Reasoning about Advisors for Seller Selection inE-Marketplaces via POMDPs (Frans A. Oliehoek and Ashwini A. Gokhale and Jie Zhang), In 15th International Workshop on Trust in Agent Societies (TRUST12), 2012. BIBTEXPDF
[146] Tree-Based Solution Methods for Multiagent POMDPswith Delayed Communication (Frans A. Oliehoek and Matthijs T. J. Spaan), In Proceedings of the National Conference on Artificial Intelligence, 2012. BIBTEXPDF
[145] Influence-Based Abstraction for Multiagent Systems (Frans A. Oliehoek and Stefan Witwicki andLeslie P. Kaelbling), In Proceedings of the National Conference on Artificial Intelligence, 2012. BIBTEXPDF

2011

[144] Scaling Up Optimal Heuristic Search in Dec-POMDPs via Incremental Expansion (Matthijs T. J. Spaan and Frans A. Oliehoek and Christopher Amato), In Proceedings of the International Joint Conference on Artificial Intelligence, 2011. BIBTEXPDF
[143] Bakebot: Baking Cookies with the PR2 (M. Bollini and J. Barry and D. Rus), In IROS PR2 Workshop, 2011. BIBTEXPDF
[142] Planning and Control under Uncertainty for the PR2 (J. Barry and M. Bollini and A. Holladay and L. Kaelbling and T. Lozano-Perez), In IROS PR2 Workshop, 2011. BIBTEXPDF
[141] Monte Carlo Pose Estimation with Quaternion Kernels and the Bingham Distribution (J. Glover and G. Bradksi and R. Rusu), In Proceedings of Robotics: Science and Systems, 2011. BIBTEXPDF
[140] Bayesian Policy Search with Policy Priors (David Wingate and Noah D. Goodman and Daniel M. Roy and Leslie P. Kaelbling and Joshua B. Tenenbaum ), In International Joint Conference on Artificial Intelligence (IJCAI), 2011. BIBTEXPDF
[139] Autonomous Skill Acquisition on a Mobile Manipulator (G.D. Konidaris and S.R. Kuindersma and R.A. Grupen and A.G. Barto), In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, 2011. BIBTEXPDF
[138] Value Function Approximation in Reinforcement Learning using the Fourier Basis (G.D. Konidaris and S. Osentoski and P.S. Thomas), In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, 2011. BIBTEXPDF
[137] TDγ: Re-evaluating Complex Backups in Temporal Difference Learning (G.D. Konidaris and S. Niekum and P.S. Thomas), In Advances in Neural Information Processing Systems 24, 2011. BIBTEXPDF
[136] CST: Constructing Skill Trees by Demonstration (G.D. Konidaris and S.R. Kuindersma and R.A. Grupen and A.G. Barto), In Proceedings of the ICML Workshop on New Developments in Imitation Learning, 2011. BIBTEXPDF
[135] Acquiring Transferrable Mobile Manipulation Skills (G.D. Konidaris and S.R. Kuindersma and R.A. Grupen and A.G. Barto), In The RSS 2011 Workshop on Mobile Manipulation: Learning to Manipulate, 2011. BIBTEXPDF
[134] Hierarchical Task and Motion Planning in the Now (Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE Conference on Robotics and Automation (ICRA), 2011. BIBTEXPDF
[133] Efficient planning in non-Gaussian belief spaces and its application to robot grasping (Robert Platt and Leslie Pack Kaelbling and Tomas Lozano-Perez and Russ Tedrake), In International Symposium on Robotics Research (ISRR), 2011. BIBTEXPDF
[132] Simultaneous localization and grasping using belief space planning (R. Platt, L. Kaelbling, T. Lozano-Perez, and R. Tedrake), In ICRA Workshop on manipulation under uncertainty, 2011. BIBTEXPDF
[131] Efficient planning in non-Gaussian belief spaces and its application to robot grasping (Robert Platt and Leslie Pack Kaelbling and Tomas Lozano-Perez and Russ Tedrake), In International Symposium on Robotics Research (ISRR), 2011. BIBTEXPDF
[130] Simultaneous localization and grasping using belief space planning (R. Platt, L. Kaelbling, T. Lozano-Perez, and R. Tedrake), In ICRA Workshop on manipulation under uncertainty, 2011. BIBTEXPDF
[129] Pre-image backchaining in belief space for mobile manipulation (Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Symposium on Robotics Research (ISRR), 2011. BIBTEXPDF
[128] DetH*: approximate Hierarchical Solution of Large Markov Decision Processes (Jennifer L. Barry and Leslie Pack Kaelbling and Tomas Lozano-Perez), In International Joint Conference on Artificial Intelligence (IJCAI), 2011. BIBTEXPDF
[127] Robust grasping under object pose uncertainty (Kaijen Hsiao and Leslie Pack Kaelbling and Tomas Lozano-Perez), In Autonomous Robots, volume 31, 2011. BIBTEXPDF
[126] CAPIR: Collaborative Action Planning with Intention Recognition (Truong-Huy Dinh Nguyen and David Hsu and Wee-Sun Lee and Tze-Yun Leong and Leslie Pack Kaelbling and Tomas Lozano-Perez and Andrew Haydn Grant), In Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE), 2011. BIBTEXPDF

2010

[125] Belief space planning assuming maximum likelihood observations (Robert Platt and Russell Tedrake and Leslie Kaelbling and Tomas Lozano-Perez), In Robotics Science and Systems Conference (RSS), 2010. BIBTEXPDF
[124] Hierarchical Solution of Large Markov Decision Processes (Jennifer L. Barry and Leslie Pack Kaelbling and Tomas Lozano-Perez), In ICAPS Workshop on Planning and Scheduling Under Uncertainty, 2010. BIBTEXPDF
[123] Task-driven Tactile Exploration (Kaijen Hsiao and Leslie Pack Kaelbling and Tomas Lozano-Perez), In Robotics Science and Systems (RSS), 2010. BIBTEXPDF
[122] Collision Avoidance for Unmanned Aircraft using Markov Decision Processes (Selim Temizer and Mykel J. Kochenderfer and Leslie Pack Kaelbling and Tomas Lozano-Perez and James K. Kuchar), In AIAA Guidance, Navigation and Control Conference, 2010. BIBTEXPDF
[121] Class-Specific Grasping of 3D Objects from a Single 2D Image (Han-Pang Chiu and Huan Liu and Leslie Kaelbling and Tomas Lozano-Perez), In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2010. BIBTEXPDF
[120] Planning in partially observable switching-mode continuous domains (Emma Brunskill and Leslie Pack Kaelbling and Tomas Lozano-Perez and Nicholas Roy), In Annals of Mathematics and Artificial Intelligence, 2010. BIBTEXPDF

2009

[119] Fast Approximate Hierarchical Solution of MDPs (J. Barry), MIT, 2009. BIBTEXPDF
[118] Learning to Generate Novel Views of Objects for Class Recognition. (Hang-Pan Chiu and Leslie P. Kaelbling andTomas Lozano-Perez), In Computer Vision and Image Understanding, 2009. BIBTEXPDF
[117] Relatively Robust Grasping (Kaijen Hsiao and Tomas Lozano-Perez and Leslie Pack Kaelbling), In International Conference on Automated Planning and Scheduling (ICAPS) Workshop on Bridging the Gap Between Task and Motion Planning, 2009. BIBTEX
[116] Segmentation According to Natural Examples: Learning StaticSegmentation from Motion Segmentation (Michael G. Ross and Leslie Pack Kaelbling), In IEEE Transactions on Pattern Analysis andMachine Intelligence, 2009. BIBTEXPDF

2008

[115] Continuous-State POMDPs with Hybrid Dynamics (Emma Brunskill and Leslie Kaelbling and Tomas Lozano-Perez and Nicholas Roy), In International Symposium on Artificial Intelligence and Mathematics, 2008. BIBTEXPDF
[114] Lifted Probabilistic Inference with Counting Formulas (Brian Milch and Luke S. Zettlemoyer and Kristian Kersting and Michael Haimes and Leslie Pack Kaelbling), In Twenty Third Conference on Artificial Intelligence (AAAI), 2008. BIBTEXPDF
[113] Robust Belief-Based Execution of Manipulation Programs (Kaijen Hsiao and Tomas Lozano-Perez and Leslie Pack Kaelbling), In Eighth International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2008. BIBTEXPDF
[112] Multi-agent Filtering with Infinitely Nested Beliefs (Luke S. Zettlemoyer and Brian Milch and Leslie PackKaelbling), In Neural Information Processing Systems (NIPS), 2008. BIBTEXPDF
[111] Automated Design of Adaptive Controllers for Modular Robots Using Reinforcement Learning (Paulina Varshasvskaya, Leslie Pack Kaelbling and Daniela Rus), In International Journal of Robotics Research, volume 27, 2008. BIBTEXPDF
[110] Efficient Distributed Reinforcement Learning Through Agreement (Paulina Varshavskaya and Leslie Pack Kaelbling and Daniela Rus), In 9th International Symposium on Distributed Autonomous Robotic Systems (DARS), 2008. BIBTEXPDF

2007

[109] Efficient Bayesian Task-level Transfer Learning (Daniel M. Roy and Leslie Pack Kaelbling), In International Joint Conference on Artificial Intelligence (IJCAI), 2007. BIBTEXPDF
[108] Learning Probabilistic Relational Dynamics for Multiple Tasks (Ashwin Deshpande and Brian Milch and Luke S. Zettlemoyer and LesliePack Kaelbling), In Conference on Uncertainty in Artificial Intelligence (UAI), 2007. BIBTEXPDF
[107] Logical Particle Filtering (Luke S. Zettlemoyer and Hanna M. Pasula and Leslie Pack Kaelbling), In Dagstuhl Seminar on Probabilistic, Logical and Relational Learning, 2007. BIBTEXPDF
[106] Action-Space Partitioning for Planning (Natalia Hernandez-Gardiol andLeslie Pack Kaelbling), In AAAI, 2007. BIBTEXPDF
[105] Grasping POMDPs: Theory and Experiments (Ross Glashan and Kaijen Hsiao and Leslie Pack Kaelbling and Tomas Lozano-Perez), In Robotics Science and Systems Manipulation Workshop: Sensing and Adapting to the Real World, 2007. BIBTEXPDF
[104] Grasping POMDPs (Kaijen Hsiao and Leslie Pack Kaelbling and Tomas Lozano-Perez), In IEEE International Conference on Robotics and Automation, 2007. BIBTEXPDF
[103] Learning Hierarchical Structure in Policies (Bhaskara Marthi and Leslie Kaelbling and Tomas Lozano-Perez), In NIPS Workshop on Hierarchical Organization of Behavior, 2007. BIBTEXPDF
[102] Learning Symbolic Models of Stochastic Domains (Hanna Pasula andLuke S. Zettlemoyer andLeslie Pack Kaelbling), In J. Artif. Intell. Res. (JAIR), volume 29, 2007. BIBTEXPDF
[101] Predicting Partial Paths from Planning Problem Parameters (Sarah Finney and Leslie Pack Kaelbling and TomasLozano-Perez), In Robotics Science and Systems, 2007. BIBTEXPDF
[100] Reasoning about Large Populations with Lifted Probabilistic Inference (Kristian Kersting and Brian Milch and Luke Zettlemoyer and Michael Haimes and Leslie Kaelbling), In NIPS Workshop on Statistical Network Models, 2007. BIBTEX
[99] Virtual Training for Multi-View Object Class Recognition. (Hang-Pan Chiu and Leslie Pack Kaelbling andTomas Lozano-Perez), In CVPR, 2007. BIBTEXPDF

2006

[98] Protein side-chain placement through MAP estimation andproblem-size reduction (Eun-Jong Hong and Tomas Lozano-Perez), In 6th Workshop on Algorithms in Bioinformatics(WABI), 2006. BIBTEXPDF
[97] Imitation Learning of Whole-Body Grasps (Kaijen Hsiao and Tomas Lozano-Perez), In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2006. BIBTEXPDF
[96] Matching Interest Points Using Affine Invariant Concentric Circles (Hang-Pan Chiu and Tomas Lozano-Perez), In Intl. Conference on Pattern Recognition (ICPR), 2006. BIBTEXPDF

2005

[95] Learning Planning Rules in Stochastic Worlds (L. Zettlemoyer and H. Pasula and L. Kaelbling), In AAAI, 2005. BIBTEXPDF
[94] Transfer Learning with an Ensemble of Background Tasks (Michael Rosenstein and Zvika Marx and Tom Dietterichand Leslie Pack Kaelbling), In NIPS Workshop on Inductive Transfer, 2005. BIBTEXPDF

2004

[93] All learning is Local: Multi-agent Learning in Global Reward Games ( Yu-Han Chang and Tracey Ho and Leslie Pack Kaelbling), In Advances in Neural Information Processing Systems 16, 2004. BIBTEXPDF
[92] Learning Probabilistic Relational Planning Rules (H. Pasula and L. Zettlemoyer and L. Kaelbling), In International Conference on Automated Planning and Scheduling (ICAPS), 2004. BIBTEXPDF
[91] Approximate Planning in POMDPs with Macro-Actions (Georgios Theocharous and Leslie Pack Kaelbling), In Advances in Neural Information Processing Systems 16 (NIPS03), 2004. BIBTEXPDF
[90] Envelope-based Planning in Relational MDPs (Natalia H. Gardiol and Leslie Pack Kaelbling), In NIPS, volume 16, 2004. BIBTEXPDF

2003

[89] A dynamical model of visually-guided steering, obstacle avoidance, and route selection (B. R. Fajen and W. H. Warren and S. Temizer and L. P. Kaelbling), In International Journal of Computer Vision, 2003. BIBTEXPDF

2002

[88] De novo determination of peptide structure with solid-state magic-angle spinning NMR spectroscopy. (C. M. Rienstra and L. Tucker-Kellogg and C. P. Jaroniec and M. Hohwy and B. Reif and M. T. McMahon and B. Tidor and T. Lozano-Perez and R. G. Griffin), In Proceedings of the National Academy of Sciences, USA, volume 99, 2002. BIBTEXPDF
[87] Learning Geometrically-Constrained Hidden Markov Models forRobot Navigation: Bridging theGeometrical-Topological Gap (Hagit Shatkay and Leslie Pack Kaelbling), In Journal of Artificial Intelligence Research, 2002. BIBTEXPDF
[86] Nearly deterministic abstractions of Markov decision processes (Terran Lane and Leslie Pack Kaelbling), In 18th National Conference on Artificial Intelligence, 2002. BIBTEXPDF

2001

[85] Visually Guided Topological Mapping for Mobile Robots (Kurt A. Steinkraus and Leslie Pack Kaelbling), In Proceedings of the SPIE, volume 4573, 2001. BIBTEX

2000

[84] Learning to Cooperate via Policy Search (Leonid Peshkin and Kee-Eung Kim and Nicolas Meuleau and Leslie Pack Kaelbling), In Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI-2000), 2000. BIBTEXPDF
[83] Practical Reinforcement Learning (William D. Smart and Leslie Pack Kaelbling), In International Conference on Machine Learning (ICML), 2000. BIBTEXPDF
[82] Sampling Methods for Action Selection in Influence Diagrams (Luis E. Ortiz andLeslie Pack Kaelbling), In AAAI/IAAI, 2000. BIBTEXPDF
[81] Image Database Retrieval With Multiple-Instance Learning Techniques (C. Yang and T. Lozano-Perez), In Intl. Conference on Data Engineering, 2000. BIBTEXPDF

1999

[80] Learning Finite-State Controllers for Partially Observable Environments. (Nicolas Meuleau and Leonid Peshkin and Kee-Eung Kim and Leslie Pack Kaelbling), In UAI, 1999. BIBTEXPDF
[79] Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs (Andrew Moore and Leemon Baird and Leslie Pack Kaelbling), In International Joint Conference on Artificial Intelligence (IJCAI), 1999. BIBTEXPDF
[78] Solving POMDPs by Searching the Space of Finite Policies (Nicolas Meuleau and Kee-Eung Kim and Leslie Pack Kaelbling and Anthony R. Cassandra), In UAI, 1999. BIBTEXPDF
[77] A Framework for Learning Query Concepts in Image Classification (A. Lakshmi-Ratan and O. Maron and W. E. L. Grimson and T. Lozano-Perez), In Computer Vision and Pattern Recognition Conference, 1999. BIBTEXPDF

1998

[76] A Framework for Multiple Instance Learning (Oded Maron and Tomas Lozano-Perez), In Advances in Neural Information Processing Systems 10, 1998. BIBTEXPDF
[75] AmbiPack: a systematic algorithm for packing of macromolecular structures withambiguous distance constraints (C.S. Wang and T. Lozano-Perez and B. Tidor ), In Proteins, volume 32, 1998. BIBTEXPDF
[74] Heading in the Right Direction (Hagit Shatkay and Leslie Pack Kaelbling), In International Conference on Machine Learning (ICML), 1998. BIBTEXPDF
[73] Hierarchical Solution of Markov Decision Processes Using MacroActions (Milos Hauskrecht and Nicolas Meuleau and Craig Boutilier and Leslie Pack Kaelbling and Thomas Dean), In Conference on Uncertainty in Artificial Intelligence (UAI), 1998. BIBTEXPDF
[72] Planning and Acting in Partially Observable Stochastic Domains (Leslie Pack Kaelbling and Michael L. Littman and Anthony R. Cassandra), In Artificial Intelligence, volume 101, 1998. BIBTEXPDF
[71] Solving Very Large Weakly Coupled Markov Decision Processes (Nicolas Meuleau and Milos Hauskrecht and Kee-Eung Kim and Leonid Peshkin and Leslie Pack Kaelbling and Thomas Dean and Craig Boutilier), In National Conference on Artificial Intelligence (AAAI), 1998. BIBTEXPDF

1997

[70] Learning Topological Maps from Weak Odometric Information (Hagit Shatkay and Leslie Pack Kaelbling), In International Joint Conference on Artificial Intelligence (IJCAI), 1997. BIBTEXPDF
[69] Solving the multiple instance problem with axis-parallel rectangles (Thomas G. Dietterich and Richard H. Lathrop and Tomas Lozano-Perez), In Artificial Intelligence, volume 89, 1997. BIBTEXPDF

1996

[68] Reinforcement Learning: A Survey (Leslie Pack Kaelbling and Michael L. Littman and Andrew P. Moore), In Journal of Artificial Intelligence Research, volume 4, 1996. BIBTEXPDF
[67] Acting under uncertainty: Discrete Bayesian models for mobile robot navigation (Anthony R. Cassandra and Leslie Pack Kaelbling and James A. Kurien), In {IEEE}/{RSJ} International Conference on Intelligent Robots and Systems (IROS), 1996. BIBTEXPDF
[66] An Automatic Registration Method for Frameless Stereotaxy, ImageGuided Surgery, and Enhanced Reality Visualization (W. Eric L. Grimson and Tomas Lozano-Perez and William M. Wells III and Gil J. Ettinger and Steve J. White and Ron Kikinis), In IEEE Transaction on Medical Imaging, volume 15, 1996. BIBTEXPDF

1995

[65] On the Complexity of Solving Markov Decision Problems (Michael L. Littman and Thomas L. Dean and Leslie Pack Kaelbling), In Proceedings of the Eleventh International Conference on Uncertainty inArtificial Intelligence, 1995. BIBTEXPDF
[64] A Situated View of Representation and Control (Stanley J. Rosenschein and Leslie Pack Kaelbling), In Artificial Intelligence, volume 72, 1995. BIBTEXPDF
[63] An Efficient Algorithm for Dynamic Programming in Partially Observable Markov Decision Processes (Michael L. Littman and Anthony R. Cassandra and Leslie Pack Kaelbling), Brown University, 1995. BIBTEX
[62] Ecological Robotics: Controlling Behavior with Optical Flow (Andrew Duchon and William Warren and Leslie Pack Kaelbling), In Proceedings of the Conference of the Cognitive Science Society, 1995. BIBTEXPDF
[61] Learning Dynamics: System Identification for Perceptually Challenged Agents (Kenneth Basye and Thomas Dean and Leslie Pack Kaelbling), In Artificial Intelligence, volume 72, 1995. BIBTEXPDF
[60] Learning Policies for Partially Observable Environments: Scaling Up (Michael L. Littman and Anthony R. Cassandra and Leslie Pack Kaelbling), In International Conference on Machine Learning (ICML), 1995. BIBTEXPDF
[59] Planning Under Time Constraints in Stochastic Domains (Thomas Dean and Leslie Pack Kaelbling and Jak Kirman and Ann Nicholson), In Artificial Intelligence, volume 76, 1995. BIBTEXPDF
[58] Two-Handed Assembly Sequencing (R. H. Wilson, and L. Kavraki and T. Lozano-Perez. and J. C. Latombe), In International Journal of Robotics Research, volume 14, 1995. BIBTEXPDF

1994

[57] Acting Optimally in Partially Observable Stochastic Domains (Anthony R. Cassandra and Leslie Pack Kaelbling and Michael L. Littman), In Proceedings of the Twelfth National Conference on Artificial Intelligence, 1994. BIBTEXPDF
[56] Algorithms for Partially Observable Markov Decision Processes (Anthony R. Cassandra and Leslie Pack Kaelbling and Michael L. Littman), Brown University, 1994. BIBTEX
[55] Associative Reinforcement Learning: A Generate and Test Algorithm (Leslie Pack Kaelbling), In Machine Learning, volume 15, 1994. BIBTEXPDF
[54] Associative Reinforcement Learning: Functions in k-DNF (Leslie Pack Kaelbling), In Machine Learning, volume 15, 1994. BIBTEXPDF
[53] Learning Hierarchies in Stochastic Domains (Leslie Pack Kaelbling and Ronny Ashar), , volume 2, 1994. BIBTEX
[52] Toward Approximate Planning in Very Large Stochastic Domains (Ann Nicholson and Leslie Pack Kaelbling), In Proceedings of the AAAI Spring Symposium on Decision Theoretic Planning, 1994. BIBTEX
[51] An Automatic Registration Methodfor Frameless Stereotaxy, Image Guided Surgery, and Enhanced RealityVisualization (W. E. L. Grimson and T. Lozano-Perez and W.M. Wells III and G.J. Ettinger andS.J. White and R. Kikinis), In Computer Vision and Pattern RecognitionConference, 1994. BIBTEXPDF

1993

[50] An Automatic Tube Inspection System that Finds Cylinders inRange Data (W.E.L.Grimson and T. Lozano-Perez and N. Noble and S.J. White), In Computer Vision and Pattern Recognition Conference (CVPR), 1993. BIBTEXPDF
[49] Deliberation Scheduling for Time-Critical Sequential Decision Making (Thomas Dean and Leslie Pack Kaelbling and Jak Kirman and Ann Nicholson), In Proceedings of the Ninth International Conference on Uncertainty in Artificial Intelligence, 1993. BIBTEXPDF
[48] Hierarchical Learning in Stochastic Domains: Preliminary Results (Leslie Pack Kaelbling), In Proceedings of the Tenth International Conference on Machine Learning, 1993. BIBTEXPDF
[47] Learning to Achieve Goals (Leslie Pack Kaelbling), In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, 1993. BIBTEXPDF
[46] Planning with Deadlines in Stochastic Domains (Thomas Dean and Leslie Pack Kaelbling and Jak Kirman and Ann Nicholson), In Proceedings of the Eleventh National Conference on Artificial Intelligence, 1993. BIBTEXPDF
[45] Assembly Sequencing for Arbitrary Motions (Tomas Lozano-Perez andRandall H. Wilson), In IEEE International Conference on Robotics and Automation, 1993. BIBTEXPDF
[44] A Comparison of Dynamic Reposing and TangentDistance for Drug Activity Prediction (T. G. Dietterich and A. Jain and R. H. Lathrop and T. Lozano-Perez), In Neural Information Processing Systems (NIPS) Conference, 1993. BIBTEXPDF

1992

[43] HANDEY: A Robot Task Planner (Tomas Lozano-Perez and Joseph L. Jones and Emanuel Mazer and Patrick A. O'Donnell), MIT Press, 1992. BIBTEXPDF

1991

[42] Compiling Operator Descriptions into Reactive Strategies using Goal Regression (Leslie Pack Kaelbling), Teleos Research, 1991. BIBTEX
[41] Foundations of Learning in Autonomous Agents (Leslie Pack Kaelbling), In Robotics and Autonomous Systems, volume 6, 1991. BIBTEX
[40] Input Generalization in Delayed Reinforcement Learning: An Algorithm and Performance Comparisons (David Chapman and Leslie Pack Kaelbling), In Proceedings of the International Joint Conference on Artificial Intelligence, 1991. BIBTEXPDF
[39] Parallel Robot Motion Planning (T. Lozano-Perez and P. A. O'Donnell), In Proceedings of the IEEE International Conference on Robotics and Automation, 1991. BIBTEXPDF

1990

[38] Action and Planning in Embedded Agents (Leslie Pack Kaelbling and Stanley J. Rosenschein), In Robotics and Autonomous Systems, volume 6, 1990. BIBTEX
[37] Integrated Agent Architectures: Benchmark Tasks and Evaluation Metrics (Mark E. Drummond and Leslie Pack Kaelbling), In Proceedings of the Workshop on Innovative Approaches to Planning, Scheduling, and Control, 1990. BIBTEX
[36] Learning Functions in k-DNF from Reinforcement (Leslie Pack Kaelbling), In Proceedings of the Seventh International Conference on Machine Learning, 1990. BIBTEX
[35] Learning in Embedded Systems (Leslie Pack Kaelbling), Stanford University, 1990. BIBTEXPDF
[34] Specifying Complex Behavior for Computer Agents (Leslie Pack Kaelbling), In Proceedings of the Workshop on Innovative Approaches to Planning, Scheduling, and Control, 1990. BIBTEX
[33] Grasp Stability and Feasibility for an Arm with and Articulated Hand (Nancy S. Pollard and Tomas Lozano-Perez), In IEEE International Conference on Robotics and Automation (ICRA), 1990. BIBTEXPDF
[32] Planning Two-Fingered Grasps for Pick-and-Place Operations on Polyhedra (Joseph L. Jones and Tomas Lozano-Perez), In IEEE International Conference on Robotics and Automation, 1990. BIBTEXPDF

1989

[31] A Formal Framework for Learning in Embedded Systems (Leslie Pack Kaelbling), In Proceedings of the Sixth International Workshop on Machine Learning, 1989. BIBTEX
[30] Integrating Planning and Reactive Control (Stanley J. Rosenschein and Leslie Pack Kaelbling), In Proceedings of NASA/JPL Conference on Space Telerobotics, 1989. BIBTEX
[29] Task-Level Planning of Pick-and-Place Robot Motions (Tomas Lozano-Perez and Joseph Jones and Emmanuel Mazer and Patrick A. O'Donnell), In IEEE Computer, volume 22, 1989. BIBTEXPDF
[28] Assembly Strategies for Chamferless Parts (Michael E Caine and Tomas Lozano-Perez and Warren P. Seering), In IEEE Robotics and Automation Conference (ICRA), 1989. BIBTEXPDF
[27] Deadlock-Free and Collision-Free Coordination of Two Robot Manipulators (Patrick A. O'Donnell and Tomas Lozano-Perez), In IEEE Robotics and Automation Conference, 1989. BIBTEXPDF

1988

[26] Goals as Parallel Program Specifications (Leslie Pack Kaelbling), In Proceedings of the Seventh National Conference on Artificial Intelligence, 1988. BIBTEX
[25] Rex Programmer’s Manual (Leslie Pack Kaelbling and Nathan J. Wilson), Artificial Intelligence Center, SRI International, 1988. BIBTEX

1987

[24] A Simple Motion Planning Algorithm for General Robot Manipulators (Tomas Lozano-Perez), In IEEE Journal of Robotics and Automation, volume 3, 1987. BIBTEXPDF
[23] An Architecture for Intelligent Reactive Systems (Leslie Pack Kaelbling), , 1987. BIBTEXPDF
[22] Learning as an Increase in Knowledge (Leslie Pack Kaelbling), Center for the Study of Language and Information, 1987. BIBTEX
[21] Localizing Overlapping Parts by Searching the Interpretation Tree (Grimson, W.E.L. and Lozano-Perez, T.), In PAMI, volume 9, 1987. BIBTEXPDF
[20] Rex: A Symbolic Language for the Design and Parallel Implementation of Embedded Systems (Leslie Pack Kaelbling), In Proceedings of the AIAA Conference on Computers in Aerospace, 1987. BIBTEX
[19] Finding Cylinders in Range Data (T. Lozano-Perez and W. E. L. Grimson and S. J. White), In International Conference on Robotics and Automation, 1987. BIBTEXPDF
[18] Regrasping (P. Tournassoud and T. Lozano-Perez and E. Mazer), In IEEE InternationalConference on Robotics and Automation, 1987. BIBTEXPDF
[17] HANDEY: A Robot System that Recognizes, Plans, and Manipulates (T. Lozano-Perez and J. L. Jones and E. Mazer and P. A. O'Donnell and W. E. L. Grimson andP. Tournassoud and A. Lanusse), In IEEE International Conference on Robotics andAutomation, 1987. BIBTEXPDF

1986

[16] On Multiple Moving Objects (Michael Erdmann and Tomas Lozano-Perez), In Algorithmica, volume 2, 1986. BIBTEXPDF
[15] The Synthesis of Digital Machines with Provable Epistemic Properties (Stanley J. Rosenschein and Leslie Pack Kaelbling), , 1986. BIBTEXPDF
[14] Off-Line Planning for On-Line Object Localization (T. Lozano-Perez and W.E.L.Grimson), In ACM/IEEE Computer Society Joint Computer Conference, 1986. BIBTEXPDF

1985

[13] Recognition and Localization of Overlapping Parts in Two and Three Dimensions (W. E. L. Grimson and T. Lozano-Perez), In IEEE International Conference on Robotics and Automation, 1985. BIBTEXPDF

1984

[12] Model-Based Recognition and Localization from Sparse Range or Tactile Data (W.E.L. Grimson and T. Lozano-Perez), In International Journal of Robotics Research, volume 3, 1984. BIBTEXPDF
[11] Automatic Synthesis of Fine-Motion Strategies for Robots (Tomas Lozano-Perez and Matthew Mason and Russell H. Taylor), In International Journal of Robotics Research, volume 3, 1984. BIBTEXPDF
[10] Tactile Recognition and Localization Using Object Models: The Case of Polyhedra on a Plane (P. C. Gaston and T. Lozano-Perez), In IEEE Trans. on PAMI, volume 6, 1984. BIBTEXPDF
[9] Model-Based Recognition and Localization from Tactile Data (W. E. L. Grimson and T. Lozano-Perez), In IEEE International Conference on Robotics and Automation, 1984. BIBTEXPDF

1983

[8] Robot Programming (Tomas Lozano-Perez), In Proceedings of the IEEE, volume 71, 1983. BIBTEXPDF
[7] A Subdivision Algorithm in Configuration Space for Findpath with Rotation (R. A. Brooks and T. Lozano-Perez), In Eighth Int. Joint Conf. on Artificial Intelligence, 1983. BIBTEXPDF
[6] Spatial Planning: A Configuration Space Approach (Tomas Lozano-Perez), In IEEE Transactions on Computers, volume 32, 1983. BIBTEXPDF

1981

[5] Automatic planning of manipulator transfer movements (Tomas Lozano-Perez), In IEEE Transactions on Systems, Man, and Cybernetics, volume 11, 1981. BIBTEXPDF

1980

[4] A Geometric Modeling System for Automated Mechanical Assembly (M. A. Wesley and T. Lozano-Perez and L. I. Lieberman and M. A. Lavin and D. D. Grossman), In IBM Journal of Rsearch and Development, volume 24, 1980. BIBTEXPDF

1979

[3] An Algorithm for Planning Collison-Free Paths Among Polyhedral Obstacles (Tomas Lozano-Perez and M. A. Wesley), In Communications of the ACM, volume 22, 1979. BIBTEXPDF

1977

[2] Parsing Intensity Profiles (Tomas Lozano-Perez), In Computer Graphics and Image Processing, volume 6, 1977. BIBTEXPDF

1974

[1] Attribute Based File Organization in a Paged Memory Environment (James B. Rothnie and Tomas Lozano), In Communications of the ACM, volume 17, 1974. BIBTEXPDF