Andrey Kolobov

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 40

Top Topics

Optimality Criteria

Planning Under Uncertainty

Reinforcement Learning

Top Venues

Publications

Florian Achermann, Thomas Stastny, Bogdan Danciu, Andrey Kolobov, Jen Jen Chung, Roland Siegwart, Nicholas R. J. Lawrance
WindSeer: Real-time volumetric wind prediction over complex terrain aboard a small UAV. CoRR (2024)
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem. CoRR (2024)
Allen Nie, Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
The Importance of Directional Feedback for LLM-based Optimizers. CoRR (2024)
Florian Achermann, Julian Andreas Haug, Tobias Zumsteg, Nicholas R. J. Lawrance, Jen Jen Chung, Andrey Kolobov, Roland Siegwart
Watching the Air Rise: Learning-Based Single-Frame Schlieren Detection. ICRA (2024)
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
Improving Offline RL by Blending Heuristics. ICLR (2024)
Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRR (2023)
Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
Interactive Robot Learning from Verbal Correction. CoRR (2023)
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
Survival Instinct in Offline Reinforcement Learning. CoRR (2023)
Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng
Improving Offline RL by Blending Heuristics. CoRR (2023)
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRR (2023)
Vinitha Ranganeni, Mike Sinclair, Eyal Ofek, Amos Miller, Jonathan Campbell, Andrey Kolobov, Edward Cutrell
Exploring Levels of Control for a Navigation Assistant for Blind Travelers. HRI (2023)
Vinitha Ranganeni, Mike Sinclair, Eyal Ofek, Amos Miller, Jonathan Campbell, Andrey Kolobov, Edward Cutrell
Exploring Levels of Control for a Navigation Assistant for Blind Travelers. CoRR (2023)
Vivek Myers, Andre Wang He, Kuan Fang, Homer Rich Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRL (2023)
Ching-An Cheng, Andrey Kolobov, Dipendra Misra, Allen Nie, Adith Swaminathan
LLF-Bench: Benchmark for Interactive Learning from Language Feedback. CoRR (2023)
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
Survival Instinct in Offline Reinforcement Learning. NeurIPS (2023)
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRL (2023)
Maxim Kuznetsov, Andrey Kolobov, Vladimir Gubernov, Andrey Polezhaev
Influence of Heat Loss on the Chaotic Dynamics of Reaction Waves in the Model with Chain-Branching Reaction. Int. J. Bifurc. Chaos 33 (12) (2023)
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. CoRR (2022)
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. NeurIPS (2022)
Bogdan Mazoure, Ahmed M Ahmed, R. Devon Hjelm, Andrey Kolobov, Patrick MacAlpine
Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL. ICLR (2022)
R. Devon Hjelm, Bogdan Mazoure, Florian Golemo, Felipe Frujeri, Mihai Jalobeanu, Andrey Kolobov
The Sandbox Environment for Generalizable Agent Research (SEGAR). CoRR (2022)
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
Heuristic-Guided Reinforcement Learning. NeurIPS (2021)
Ching-An Cheng, Andrey Kolobov, Adith Swaminathan
Heuristic-Guided Reinforcement Learning. CoRR (2021)
Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. 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
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. CoRR (2021)
Bogdan Mazoure, Ahmed M. Ahmed, Patrick MacAlpine, R. Devon Hjelm, Andrey Kolobov
Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL. CoRR (2021)
Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. 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
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. NeurIPS (Competition and Demos) (2020)
Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
Safe Reinforcement Learning via Curriculum Induction. NeurIPS (2020)
Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
Online Learning for Active Cache Synchronization. CoRR (2020)
Florian Achermann, Andrey Kolobov, Debadeepta Dey, Timo Hinzmann, Jen Jen Chung, Roland Siegwart, Nicholas R. J. Lawrance
MultiPoint: Cross-spectral registration of thermal and optical aerial imagery. CoRL (2020)
Andrey Kolobov, Sébastien Bubeck, Julian Zimmert
Online Learning for Active Cache Synchronization. ICML (2020)
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
Policy Improvement from Multiple Experts. CoRR (2020)
Ching-An Cheng, Andrey Kolobov, Alekh Agarwal
Policy Improvement via Imitation of Multiple Oracles. NeurIPS (2020)
Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal
Safe Reinforcement Learning via Curriculum Induction. CoRR (2020)
Andrey Kolobov, Yuval Peres, Cheng Lu, Eric Horvitz
Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling. NeurIPS (2019)
Andrey Kolobov, Yuval Peres, Eyal Lubetzky, Eric Horvitz
Optimal Freshness Crawl Under Politeness Constraints. SIGIR (2019)
Iain Guilliard, Richard Rogahn, Jim Piavis, Andrey Kolobov
Autonomous Thermalling as a Partially Observable Markov Decision Process (Extended Version). CoRR (2018)
Iain Guilliard, Richard Rogahn, Jim Piavis, Andrey Kolobov
Autonomous Thermalling as a Partially Observable Markov Decision Process. Robotics: Science and Systems (2018)
Samuel Tabor, Iain Guilliard, Andrey Kolobov
ArduSoar: An Open-Source Thermalling Controller for Resource-Constrained Autopilots. IROS (2018)
Samuel Tabor, Iain Guilliard, Andrey Kolobov
ArduSoar: an Open-Source Thermalling Controller for Resource-Constrained Autopilots. CoRR (2018)
Ofra Amir, Ece Kamar, Andrey Kolobov, Barbara J. Grosz
Interactive Teaching Strategies for Agent Training. IJCAI (2016)
Jan Van Haaren, Andrey Kolobov, Jesse Davis
TODTLER: Two-Order-Deep Transfer Learning. AAAI (2015)
Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz
Metareasoning for Planning Under Uncertainty. CoRR (2015)
Abdelrahman Elogeel, Andrey Kolobov, Matthew Alden, Ankur Teredesai
Selecting Robust Strategies in RTS Games via Concurrent Plan Augmentation. AAMAS (2015)
Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz
Metareasoning for Planning Under Uncertainty. IJCAI (2015)
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
Gauss meets Canadian traveler: shortest-path problems with correlated natural dynamics. AAMAS (2014)
Jonathan Bragg, Andrey Kolobov, Mausam, Daniel S. Weld
Parallel Task Routing for Crowdsourcing. HCOMP (2014)
Jonathan Sprauel, Andrey Kolobov, Florent Teichteil-Königsbuch
Saturated Path-Constrained MDP: Planning under Uncertainty and Deterministic Model-Checking Constraints. AAAI (2014)
Andrey Kolobov, Mausam, Daniel S. Weld
Joint Crowdsourcing of Multiple Tasks. HCOMP (Works in Progress / Demos) (2013)
Andrey Kolobov, Mausam, Daniel S. Weld
A Theory of Goal-Oriented MDPs with Dead Ends. UAI (2012)
Andrey Kolobov, Mausam, Daniel S. Weld
LRTDP Versus UCT for Online Probabilistic Planning. AAAI (2012)
Andrey Kolobov, Mausam, Daniel S. Weld
A Theory of Goal-Oriented MDPs with Dead Ends CoRR (2012)
Andrey Kolobov, Peng Dai, Mausam, Daniel S. Weld
Reverse Iterative Deepening for Finite-Horizon MDPs with Large Branching Factors. ICAPS (2012)
Andrey Kolobov, Mausam, Daniel S. Weld
Discovering hidden structure in factored MDPs. Artif. Intell. 189 (2012)
Andrey Kolobov, Mausam, Daniel S. Weld
Towards Scalable MDP Algorithms. IJCAI (2011)
Andrey Kolobov, Mausam, Daniel S. Weld, Hector Geffner
Heuristic Search for Generalized Stochastic Shortest Path MDPs. ICAPS (2011)
Andrey Kolobov, Mausam, Daniel S. Weld
SixthSense: Fast and Reliable Recognition of Dead Ends in MDPs. AAAI (2010)
Andrey Kolobov, Mausam, Daniel S. Weld
Classical Planning in MDP Heuristics: with a Little Help from Generalization. ICAPS (2010)
Andrey Kolobov, Mausam, Daniel S. Weld
ReTrASE: Integrating Paradigms for Approximate Probabilistic Planning. IJCAI (2009)
Brian Milch, Bhaskara Marthi, Stuart J. Russell, David A. Sontag, Daniel L. Ong, Andrey Kolobov
BLOG: Probabilistic Models with Unknown Objects. Probabilistic, Logical and Relational Learning (2005)
Brian Milch, Bhaskara Marthi, Stuart J. Russell, David A. Sontag, Daniel L. Ong, Andrey Kolobov
BLOG: Probabilistic Models with Unknown Objects. IJCAI (2005)
Brian Milch, Bhaskara Marthi, David A. Sontag, Stuart J. Russell, Daniel L. Ong, Andrey Kolobov
Approximate Inference for Infinite Contingent Bayesian Networks. AISTATS (2005)