PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | June 2024
ORAL
Andrey Kolobov
Directeur principal de la recherche
Papiers de Collaboration
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Rapidly Adapting Policies to the Real World via Simulation-Guided Fine-Tuning
Patrick Yin, Tyler Westenbroek, Simran Bagaria, Kevin Huang, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta
Under submission | June 2024
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Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Open X-Embodiment Collaboration, Abby O'Neill, Abdul Rehman, Abhinav Gupta, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alex Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Andrey Kolobov, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Felipe Vieira Frujeri, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guangwen Yang, Guanzhi Wang, Hao Su, Hao-Shu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I Christensen, Hiroki Furuta, Homanga Bharadhwaj, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jay Vakil, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi "Jim" Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J Joshi, Niko Suenderhauf, Ning Liu, Norman Di Palo, Nur Muhammad Mahi Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R Sanketi, Patrick "Tree" Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Mart'in-Mart'in, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham Sonawani, Shubham Tulsiani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vikash Kumar, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiangyu Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Xu Liangwei, Xuanlin Li, Yansong Pang, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yongqiang Dou, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Fu, Zipeng Lin
arXiv | June 2024
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WindSeer: Real-time volumetric wind prediction over complex terrain aboard a small uncrewed aerial vehicle
Florian Achermann, Thomas Stastny, Bogdan Danciu, Andrey Kolobov, Jen Jen Chung, Roland Siegwart, Nicholas Lawrance
Nature Communications | May 2024
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Watching the Air Rise: Learning-Based Single-Frame Schlieren Detection
Florian Achermann, Julian Andreas Haug, Tobias Zumsteg, Nicholas Lawrance, Jen Jen Chung, Andrey Kolobov, Roland Siegwart
ICRA 2024 | May 2024
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Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
ICLR 2024 | May 2024
SPOTLIGHT
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Importance of Directional Feedback for LLM-based Optimizers
Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2023 Foundation Models for Decision Making Workshop | December 2023
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LLF-Bench: Benchmark for Interactive Learning from Language Feedback
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
December 2023
December 2023
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Survival Instinct in Offline Reinforcement Learning
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
NeurIPS 2023 | December 2023
SPOTLIGHT
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Interactive Robot Learning from Verbal Correction
Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
CoRL 2023 Workshop on Language and Robot Learning (LangRob) | November 2023
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Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca Dragan, Sergey Levine
CoRL 2023 | June 2023
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PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
CoRL 2023 | June 2023
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Survival Instinct in Offline Reinforcement Learning and Implicit Human Bias in Data
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
ICML 2023 - Interactive Learning with Implicit Human Feedback Workshop | June 2023
ORAL
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Exploring Levels of Control for a Navigation Assistant for Blind Travelers
Vinitha Ranganeni, Mike Sinclair, Eyal Ofek, Amos Miller, Jon Campbell, Andrey Kolobov, Ed Cutrell
HRI 2023 | March 2023
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MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew Hausknecht
NeurIPS 2022 Datasets and Benchmarks Track | July 2022
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Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL
Bogdan Mazoure, Ahmed Ahmed, Patrick MacAlpine, Devon Hjelm, Andrey Kolobov
ICLR 2022 | April 2022
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The Sandbox Environment for Generalizable Agent Research (SEGAR)
R Devon Hjelm, Bogdan Mazoure, Florian Golemo, Felipe Vieira Frujeri, Mihai Jalobeanu, Andrey Kolobov
March 2022
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Heuristic-Guided Reinforcement Learning
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2021 | December 2021
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Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark
Sharada Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Gražvydas Šemetulskis, João Schapke, Jonas Kubilius, Jurgis Pašukonis, Linas Klimas, Matthew Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe
NeurIPS 2020 Competition Track | March 2021
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Policy Improvement via Imitation of Multiple Oracles
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
NeurIPS 2020 | December 2020
SPOTLIGHT
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Safe Reinforcement Learning via Curriculum Induction
Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
NeurIPS 2020 | December 2020
SPOTLIGHT
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MultiPoint: Cross-spectral registration of thermal and optical aerial imagery
Florian Achermann, Andrey Kolobov, Debadeepta Dey, Timo Hinzmann, Jen Jen Chung, Roland Siegwart, Nicholas Lawrance
CoRL 2020 | November 2020
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Online Learning for Active Cache Synchronization
Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
ICML 2020 | July 2020
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Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling
Andrey Kolobov, Yuval Peres, Cheng Lu, Eric Horvitz
NeurIPS 2019 | October 2019
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Optimal Freshness Crawl Under Politeness Constraints
Andrey Kolobov, Yuval Peres, Eyal Lubetzky, Eric Horvitz
SIGIR 2019 | July 2019
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ArduSoar: an Open-Source Thermalling Controller for Resource-Constrained Autopilots
Samuel Tabor, Iain Guilliard, Andrey Kolobov
IROS 2018 | October 2018
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Autonomous Thermalling as a Partially Observable Markov Decision Process
Iain Guilliard, Rick Rogahn, Jim Piavis, Andrey Kolobov
RSS 2018 | June 2018
Invited for AURO special issue as one of the top RSS 2018 papers
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Interactive Teaching Strategies for Agent Training
Ofra Amir, Ece Kamar, Andrey Kolobov, Barbara Grosz
IJCAI 2016 | May 2016
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Metareasoning for Planning Under Uncertainty
Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz
IJCAI 2015 | July 2015
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Selecting Robust Strategies in RTS Games via Concurrent Plan Augmentation
Abdelrahman Elogeel, Andrey Kolobov, Matthew Alden, Ankur Teredesai
AAMAS 2015 | May 2015
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TODTLER: Two-Order-Deep Transfer Learning
Jan Van Haaren, Andrey Kolobov, Jesse Davis
AAAI 2015 | January 2015
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Parallel Task Routing for Crowdsourcing
Jonathan Bragg, Andrey Kolobov, Mausam, Daniel Weld
HCOMP 2014 | November 2014
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Saturated Path-Constrained MDP: Planning Under Uncertainty and Deterministic Model-Checking Constraints
Jonathan Sprauel, Andrey Kolobov, Florent Teichteil-Königsbuch
AAAI 2014 | July 2014
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Gauss Meets Canadian Traveler: Shortest-Path Problems with Correlated Natural Dynamics
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
AAMAS 2014 | May 2014
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Joint Crowdsourcing of Multiple Tasks
Andrey Kolobov, Mausam, Daniel S. Weld
HCOMP 2013 | November 2013
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Scalable Methods and Expressive Models for Planning Under Uncertainty
June 2013, pp. 1-274
June 2013
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Discovering Hidden Structure in Factored MDPs
Andrey Kolobov, Mausam, Daniel S. Weld
Artificial Intelligence Journal (AIJ) | September 2012, Vol 189: pp. 19-47
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A Theory of Goal-Oriented MDPs with Dead Ends
Andrey Kolobov, Mausam, Daniel S. Weld
UAI 2012 | August 2012
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LRTDP vs. UCT for Online Probabilistic Planning
Andrey Kolobov, Mausam, Daniel S. Weld
AAAI 2012 | July 2012
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Reverse Iterative Deepening for Finite-Horizon MDPs with Large Branching Factors
Andrey Kolobov, Peng Dai, Mausam, Daniel S. Weld
ICAPS 2012 | June 2012
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Planning with Markov Decision Processes: An AI Perspective
Mausam, Andrey Kolobov
Synthesis Lectures on Artificial Intelligence and Machine Learning | Publié par Morgan & Claypool Publishers | 2012
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Towards Scalable MDP Algorithms
Andrey Kolobov, Mausam, Daniel S. Weld
IJCAI 2011 Doctoral Consortium | July 2011
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Heuristic Search for Generalized Stochastic Shortest Path MDPs
Andrey Kolobov, Mausam, Daniel S. Weld, Hector Geffner
ICAPS 2011 | June 2011
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SixthSense: Fast and Reliable Recognition of Dead Ends in MDPs
Andrey Kolobov, Mausam, Daniel S. Weld
AAAI 2010 | July 2010
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Classical Planning in MDP Heuristics: With a Little Help from Generalization
Andrey Kolobov, Mausam, Daniel S. Weld
ICAPS 2010 | May 2010
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Determinize, Solve, and Generalize: Classical Planning for MDP Heuristics
Andrey Kolobov, Mausam, Daniel S. Weld
ICAPS 2009 Workshop on Heuristics for Domain Independent Planning | September 2009
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ReTrASE: Intergating Paradigms for Approximate Probabilistic Planning
Andrey Kolobov, Mausam, Daniel S. Weld
IJCAI 2009 | July 2009
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Regressing Deterministic Plans for MDP Function Approximation
Andrey Kolobov, Mausam, Daniel S. Weld
ICAPS 2008 Workshop on A Reality Check for Planning and Scheduling Under Uncertainty | September 2008
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BLOG: Probabilistic Models with Unknown Objects
Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, Andrey Kolobov
Introduction to Statistical Relational Learning | Publié par MIT Press | 2007
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BLOG: Probabilistic Models with Unknown Objects
Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, Andrey Kolobov
IJCAI 2005 | July 2005
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Approximate Inference for Infinite Contingent Bayesian Networks
Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov
AISTATS 2005 | January 2005
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PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | June 2024
ORAL
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Rapidly Adapting Policies to the Real World via Simulation-Guided Fine-Tuning
Patrick Yin, Tyler Westenbroek, Simran Bagaria, Kevin Huang, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta
Under submission | June 2024
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Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Open X-Embodiment Collaboration, Abby O'Neill, Abdul Rehman, Abhinav Gupta, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alex Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Andrey Kolobov, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Felipe Vieira Frujeri, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guangwen Yang, Guanzhi Wang, Hao Su, Hao-Shu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I Christensen, Hiroki Furuta, Homanga Bharadhwaj, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jay Vakil, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi "Jim" Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J Joshi, Niko Suenderhauf, Ning Liu, Norman Di Palo, Nur Muhammad Mahi Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R Sanketi, Patrick "Tree" Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Mart'in-Mart'in, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham Sonawani, Shubham Tulsiani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vikash Kumar, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiangyu Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Xu Liangwei, Xuanlin Li, Yansong Pang, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yongqiang Dou, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Fu, Zipeng Lin
arXiv | June 2024
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WindSeer: Real-time volumetric wind prediction over complex terrain aboard a small uncrewed aerial vehicle
Florian Achermann, Thomas Stastny, Bogdan Danciu, Andrey Kolobov, Jen Jen Chung, Roland Siegwart, Nicholas Lawrance
Nature Communications | May 2024
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Watching the Air Rise: Learning-Based Single-Frame Schlieren Detection
Florian Achermann, Julian Andreas Haug, Tobias Zumsteg, Nicholas Lawrance, Jen Jen Chung, Andrey Kolobov, Roland Siegwart
ICRA 2024 | May 2024
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Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
ICLR 2024 | May 2024
SPOTLIGHT
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Importance of Directional Feedback for LLM-based Optimizers
Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2023 Foundation Models for Decision Making Workshop | December 2023
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LLF-Bench: Benchmark for Interactive Learning from Language Feedback
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
December 2023
December 2023
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Survival Instinct in Offline Reinforcement Learning
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
NeurIPS 2023 | December 2023
SPOTLIGHT
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Interactive Robot Learning from Verbal Correction
Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
CoRL 2023 Workshop on Language and Robot Learning (LangRob) | November 2023
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Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca Dragan, Sergey Levine
CoRL 2023 | June 2023
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PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
CoRL 2023 | June 2023
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Survival Instinct in Offline Reinforcement Learning and Implicit Human Bias in Data
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
ICML 2023 - Interactive Learning with Implicit Human Feedback Workshop | June 2023
ORAL
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Exploring Levels of Control for a Navigation Assistant for Blind Travelers
Vinitha Ranganeni, Mike Sinclair, Eyal Ofek, Amos Miller, Jon Campbell, Andrey Kolobov, Ed Cutrell
HRI 2023 | March 2023
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MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew Hausknecht
NeurIPS 2022 Datasets and Benchmarks Track | July 2022
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Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL
Bogdan Mazoure, Ahmed Ahmed, Patrick MacAlpine, Devon Hjelm, Andrey Kolobov
ICLR 2022 | April 2022
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The Sandbox Environment for Generalizable Agent Research (SEGAR)
R Devon Hjelm, Bogdan Mazoure, Florian Golemo, Felipe Vieira Frujeri, Mihai Jalobeanu, Andrey Kolobov
March 2022
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Heuristic-Guided Reinforcement Learning
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2021 | December 2021
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Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark
Sharada Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Gražvydas Šemetulskis, João Schapke, Jonas Kubilius, Jurgis Pašukonis, Linas Klimas, Matthew Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe
NeurIPS 2020 Competition Track | March 2021
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Policy Improvement via Imitation of Multiple Oracles
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
NeurIPS 2020 | December 2020
SPOTLIGHT
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Safe Reinforcement Learning via Curriculum Induction
Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
NeurIPS 2020 | December 2020
SPOTLIGHT
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MultiPoint: Cross-spectral registration of thermal and optical aerial imagery
Florian Achermann, Andrey Kolobov, Debadeepta Dey, Timo Hinzmann, Jen Jen Chung, Roland Siegwart, Nicholas Lawrance
CoRL 2020 | November 2020
-
Online Learning for Active Cache Synchronization
Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
ICML 2020 | July 2020
-
Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling
Andrey Kolobov, Yuval Peres, Cheng Lu, Eric Horvitz
NeurIPS 2019 | October 2019
-
ArduSoar: an Open-Source Thermalling Controller for Resource-Constrained Autopilots
Samuel Tabor, Iain Guilliard, Andrey Kolobov
IROS 2018 | October 2018
-
Autonomous Thermalling as a Partially Observable Markov Decision Process
Iain Guilliard, Rick Rogahn, Jim Piavis, Andrey Kolobov
RSS 2018 | June 2018
Invited for AURO special issue as one of the top RSS 2018 papers
-
Interactive Teaching Strategies for Agent Training
Ofra Amir, Ece Kamar, Andrey Kolobov, Barbara Grosz
IJCAI 2016 | May 2016
-
Metareasoning for Planning Under Uncertainty
Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz
IJCAI 2015 | July 2015
-
TODTLER: Two-Order-Deep Transfer Learning
Jan Van Haaren, Andrey Kolobov, Jesse Davis
AAAI 2015 | January 2015
-
Parallel Task Routing for Crowdsourcing
Jonathan Bragg, Andrey Kolobov, Mausam, Daniel Weld
HCOMP 2014 | November 2014
-
Saturated Path-Constrained MDP: Planning Under Uncertainty and Deterministic Model-Checking Constraints
Jonathan Sprauel, Andrey Kolobov, Florent Teichteil-Königsbuch
AAAI 2014 | July 2014
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Gauss Meets Canadian Traveler: Shortest-Path Problems with Correlated Natural Dynamics
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
AAMAS 2014 | May 2014
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Scalable Methods and Expressive Models for Planning Under Uncertainty
June 2013, pp. 1-274
June 2013
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Discovering Hidden Structure in Factored MDPs
Andrey Kolobov, Mausam, Daniel S. Weld
Artificial Intelligence Journal (AIJ) | September 2012, Vol 189: pp. 19-47
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A Theory of Goal-Oriented MDPs with Dead Ends
Andrey Kolobov, Mausam, Daniel S. Weld
UAI 2012 | August 2012
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LRTDP vs. UCT for Online Probabilistic Planning
Andrey Kolobov, Mausam, Daniel S. Weld
AAAI 2012 | July 2012
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Planning with Markov Decision Processes: An AI Perspective
Mausam, Andrey Kolobov
Synthesis Lectures on Artificial Intelligence and Machine Learning | Publié par Morgan & Claypool Publishers | 2012
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Towards Scalable MDP Algorithms
Andrey Kolobov, Mausam, Daniel S. Weld
IJCAI 2011 Doctoral Consortium | July 2011
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Heuristic Search for Generalized Stochastic Shortest Path MDPs
Andrey Kolobov, Mausam, Daniel S. Weld, Hector Geffner
ICAPS 2011 | June 2011
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SixthSense: Fast and Reliable Recognition of Dead Ends in MDPs
Andrey Kolobov, Mausam, Daniel S. Weld
AAAI 2010 | July 2010
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Classical Planning in MDP Heuristics: With a Little Help from Generalization
Andrey Kolobov, Mausam, Daniel S. Weld
ICAPS 2010 | May 2010
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Determinize, Solve, and Generalize: Classical Planning for MDP Heuristics
Andrey Kolobov, Mausam, Daniel S. Weld
ICAPS 2009 Workshop on Heuristics for Domain Independent Planning | September 2009
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ReTrASE: Intergating Paradigms for Approximate Probabilistic Planning
Andrey Kolobov, Mausam, Daniel S. Weld
IJCAI 2009 | July 2009
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Regressing Deterministic Plans for MDP Function Approximation
Andrey Kolobov, Mausam, Daniel S. Weld
ICAPS 2008 Workshop on A Reality Check for Planning and Scheduling Under Uncertainty | September 2008
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BLOG: Probabilistic Models with Unknown Objects
Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, Andrey Kolobov
IJCAI 2005 | July 2005
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Approximate Inference for Infinite Contingent Bayesian Networks
Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov
AISTATS 2005 | January 2005
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MultiPoint: Cross-spectral registration of thermal and optical aerial imagery
Florian Achermann, Andrey Kolobov, Debadeepta Dey, Timo Hinzmann, Jen Jen Chung, Roland Siegwart, Nicholas Lawrance
CoRL 2020 | November 2020
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Gauss Meets Canadian Traveler: Shortest-Path Problems with Correlated Natural Dynamics
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
AAMAS 2014 | May 2014
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Online Learning for Active Cache Synchronization
Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
ICML 2020 | July 2020
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Optimal Freshness Crawl Under Politeness Constraints
Andrey Kolobov, Yuval Peres, Eyal Lubetzky, Eric Horvitz
SIGIR 2019 | July 2019
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Selecting Robust Strategies in RTS Games via Concurrent Plan Augmentation
Abdelrahman Elogeel, Andrey Kolobov, Matthew Alden, Ankur Teredesai
AAMAS 2015 | May 2015
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Joint Crowdsourcing of Multiple Tasks
Andrey Kolobov, Mausam, Daniel S. Weld
HCOMP 2013 | November 2013
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Reverse Iterative Deepening for Finite-Horizon MDPs with Large Branching Factors
Andrey Kolobov, Peng Dai, Mausam, Daniel S. Weld
ICAPS 2012 | June 2012
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BLOG: Probabilistic Models with Unknown Objects
Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, Andrey Kolobov
Introduction to Statistical Relational Learning | Publié par MIT Press | 2007
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Joint Crowdsourcing of Multiple Tasks
Andrey Kolobov, Mausam, Daniel S. Weld
HCOMP 2013 | November 2013
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PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | June 2024
ORAL
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Rapidly Adapting Policies to the Real World via Simulation-Guided Fine-Tuning
Patrick Yin, Tyler Westenbroek, Simran Bagaria, Kevin Huang, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta
Under submission | June 2024
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Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Open X-Embodiment Collaboration, Abby O'Neill, Abdul Rehman, Abhinav Gupta, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alex Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Andrey Kolobov, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Felipe Vieira Frujeri, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guangwen Yang, Guanzhi Wang, Hao Su, Hao-Shu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I Christensen, Hiroki Furuta, Homanga Bharadhwaj, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jay Vakil, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi "Jim" Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J Joshi, Niko Suenderhauf, Ning Liu, Norman Di Palo, Nur Muhammad Mahi Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R Sanketi, Patrick "Tree" Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Mart'in-Mart'in, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham Sonawani, Shubham Tulsiani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vikash Kumar, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiangyu Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Xu Liangwei, Xuanlin Li, Yansong Pang, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yongqiang Dou, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Fu, Zipeng Lin
arXiv | June 2024
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Watching the Air Rise: Learning-Based Single-Frame Schlieren Detection
Florian Achermann, Julian Andreas Haug, Tobias Zumsteg, Nicholas Lawrance, Jen Jen Chung, Andrey Kolobov, Roland Siegwart
ICRA 2024 | May 2024
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Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
ICLR 2024 | May 2024
SPOTLIGHT
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Importance of Directional Feedback for LLM-based Optimizers
Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2023 Foundation Models for Decision Making Workshop | December 2023
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Survival Instinct in Offline Reinforcement Learning
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
NeurIPS 2023 | December 2023
SPOTLIGHT
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Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca Dragan, Sergey Levine
CoRL 2023 | June 2023
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PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
CoRL 2023 | June 2023
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Survival Instinct in Offline Reinforcement Learning and Implicit Human Bias in Data
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
ICML 2023 - Interactive Learning with Implicit Human Feedback Workshop | June 2023
ORAL
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Exploring Levels of Control for a Navigation Assistant for Blind Travelers
Vinitha Ranganeni, Mike Sinclair, Eyal Ofek, Amos Miller, Jon Campbell, Andrey Kolobov, Ed Cutrell
HRI 2023 | March 2023
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MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew Hausknecht
NeurIPS 2022 Datasets and Benchmarks Track | July 2022
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Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL
Bogdan Mazoure, Ahmed Ahmed, Patrick MacAlpine, Devon Hjelm, Andrey Kolobov
ICLR 2022 | April 2022
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Heuristic-Guided Reinforcement Learning
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
NeurIPS 2021 | December 2021
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Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark
Sharada Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Gražvydas Šemetulskis, João Schapke, Jonas Kubilius, Jurgis Pašukonis, Linas Klimas, Matthew Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe
NeurIPS 2020 Competition Track | March 2021
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Policy Improvement via Imitation of Multiple Oracles
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
NeurIPS 2020 | December 2020
SPOTLIGHT
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Safe Reinforcement Learning via Curriculum Induction
Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
NeurIPS 2020 | December 2020
SPOTLIGHT
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MultiPoint: Cross-spectral registration of thermal and optical aerial imagery
Florian Achermann, Andrey Kolobov, Debadeepta Dey, Timo Hinzmann, Jen Jen Chung, Roland Siegwart, Nicholas Lawrance
CoRL 2020 | November 2020
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Online Learning for Active Cache Synchronization
Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
ICML 2020 | July 2020
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Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling
Andrey Kolobov, Yuval Peres, Cheng Lu, Eric Horvitz
NeurIPS 2019 | October 2019
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Optimal Freshness Crawl Under Politeness Constraints
Andrey Kolobov, Yuval Peres, Eyal Lubetzky, Eric Horvitz
SIGIR 2019 | July 2019
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ArduSoar: an Open-Source Thermalling Controller for Resource-Constrained Autopilots
Samuel Tabor, Iain Guilliard, Andrey Kolobov
IROS 2018 | October 2018
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Autonomous Thermalling as a Partially Observable Markov Decision Process
Iain Guilliard, Rick Rogahn, Jim Piavis, Andrey Kolobov
RSS 2018 | June 2018
Invited for AURO special issue as one of the top RSS 2018 papers
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Interactive Teaching Strategies for Agent Training
Ofra Amir, Ece Kamar, Andrey Kolobov, Barbara Grosz
IJCAI 2016 | May 2016
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Metareasoning for Planning Under Uncertainty
Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz
IJCAI 2015 | July 2015
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Selecting Robust Strategies in RTS Games via Concurrent Plan Augmentation
Abdelrahman Elogeel, Andrey Kolobov, Matthew Alden, Ankur Teredesai
AAMAS 2015 | May 2015
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TODTLER: Two-Order-Deep Transfer Learning
Jan Van Haaren, Andrey Kolobov, Jesse Davis
AAAI 2015 | January 2015
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Parallel Task Routing for Crowdsourcing
Jonathan Bragg, Andrey Kolobov, Mausam, Daniel Weld
HCOMP 2014 | November 2014
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Saturated Path-Constrained MDP: Planning Under Uncertainty and Deterministic Model-Checking Constraints
Jonathan Sprauel, Andrey Kolobov, Florent Teichteil-Königsbuch
AAAI 2014 | July 2014
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Gauss Meets Canadian Traveler: Shortest-Path Problems with Correlated Natural Dynamics
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
AAMAS 2014 | May 2014
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Joint Crowdsourcing of Multiple Tasks
Andrey Kolobov, Mausam, Daniel S. Weld
HCOMP 2013 | November 2013
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A Theory of Goal-Oriented MDPs with Dead Ends
Andrey Kolobov, Mausam, Daniel S. Weld
UAI 2012 | August 2012
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LRTDP vs. UCT for Online Probabilistic Planning
Andrey Kolobov, Mausam, Daniel S. Weld
AAAI 2012 | July 2012
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Reverse Iterative Deepening for Finite-Horizon MDPs with Large Branching Factors
Andrey Kolobov, Peng Dai, Mausam, Daniel S. Weld
ICAPS 2012 | June 2012
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Towards Scalable MDP Algorithms
Andrey Kolobov, Mausam, Daniel S. Weld
IJCAI 2011 Doctoral Consortium | July 2011
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Heuristic Search for Generalized Stochastic Shortest Path MDPs
Andrey Kolobov, Mausam, Daniel S. Weld, Hector Geffner
ICAPS 2011 | June 2011
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SixthSense: Fast and Reliable Recognition of Dead Ends in MDPs
Andrey Kolobov, Mausam, Daniel S. Weld
AAAI 2010 | July 2010
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Classical Planning in MDP Heuristics: With a Little Help from Generalization
Andrey Kolobov, Mausam, Daniel S. Weld
ICAPS 2010 | May 2010
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Determinize, Solve, and Generalize: Classical Planning for MDP Heuristics
Andrey Kolobov, Mausam, Daniel S. Weld
ICAPS 2009 Workshop on Heuristics for Domain Independent Planning | September 2009
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ReTrASE: Intergating Paradigms for Approximate Probabilistic Planning
Andrey Kolobov, Mausam, Daniel S. Weld
IJCAI 2009 | July 2009
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Regressing Deterministic Plans for MDP Function Approximation
Andrey Kolobov, Mausam, Daniel S. Weld
ICAPS 2008 Workshop on A Reality Check for Planning and Scheduling Under Uncertainty | September 2008
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BLOG: Probabilistic Models with Unknown Objects
Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, Andrey Kolobov
IJCAI 2005 | July 2005
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Approximate Inference for Infinite Contingent Bayesian Networks
Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov
AISTATS 2005 | January 2005
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WindSeer: Real-time volumetric wind prediction over complex terrain aboard a small uncrewed aerial vehicle
Florian Achermann, Thomas Stastny, Bogdan Danciu, Andrey Kolobov, Jen Jen Chung, Roland Siegwart, Nicholas Lawrance
Nature Communications | May 2024
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Interactive Robot Learning from Verbal Correction
Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
CoRL 2023 Workshop on Language and Robot Learning (LangRob) | November 2023
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Discovering Hidden Structure in Factored MDPs
Andrey Kolobov, Mausam, Daniel S. Weld
Artificial Intelligence Journal (AIJ) | September 2012, Vol 189: pp. 19-47
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LLF-Bench: Benchmark for Interactive Learning from Language Feedback
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
December 2023
December 2023
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The Sandbox Environment for Generalizable Agent Research (SEGAR)
R Devon Hjelm, Bogdan Mazoure, Florian Golemo, Felipe Vieira Frujeri, Mihai Jalobeanu, Andrey Kolobov
March 2022
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Scalable Methods and Expressive Models for Planning Under Uncertainty
June 2013, pp. 1-274
June 2013
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Planning with Markov Decision Processes: An AI Perspective
Mausam, Andrey Kolobov
Synthesis Lectures on Artificial Intelligence and Machine Learning | Publié par Morgan & Claypool Publishers | 2012
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BLOG: Probabilistic Models with Unknown Objects
Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong, Andrey Kolobov
Introduction to Statistical Relational Learning | Publié par MIT Press | 2007
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