41 Results

Poster
Tue 7:00 Evaluating the Performance of Reinforcement Learning Algorithms
Scott M Jordan, Yash Chandak, Daniel Cohen, Mengxue Zhang, Philip Thomas
Poster
Tue 7:00 Private Reinforcement Learning with PAC and Regret Guarantees
Giuseppe Vietri, Borja de Balle Pigem, Akshay Krishnamurthy, Steven Wu
Poster
Tue 7:00 Optimizing for the Future in Non-Stationary MDPs
Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip Thomas
Poster
Tue 7:00 Asynchronous Coagent Networks
James Kostas, Chris Nota, Philip Thomas
Poster
Tue 8:00 Batch Reinforcement Learning with Hyperparameter Gradients
Byung-Jun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim
Poster
Tue 8:00 FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis
Aman Sinha, Matthew O'Kelly, Hongrui Zheng, Rahul Mangharam, John Duchi, Russ Tedrake
Poster
Tue 8:00 Representations for Stable Off-Policy Reinforcement Learning
Dibya Ghosh, Marc Bellemare
Poster
Tue 8:00 Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Ron Meir, Kamil Ciosek
Poster
Tue 9:00 Lookahead-Bounded Q-learning
Ibrahim El Shar, Daniel Jiang
Poster
Tue 9:00 Tightening Exploration in Upper Confidence Reinforcement Learning
Hippolyte Bourel, Odalric-Ambrym Maillard, Mohammad Sadegh Talebi
Poster
Tue 9:00 Structured Policy Iteration for Linear Quadratic Regulator
Youngsuk Park, Ryan Rossi, Zheng Wen, Gang Wu, Handong Zhao
Poster
Tue 10:00 Sub-Goal Trees -- a Framework for Goal-Based Reinforcement Learning
Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar
Poster
Tue 10:00 Selective Dyna-style Planning Under Limited Model Capacity
Zaheer Abbas, Samuel Sokota, Erin Talvitie, Martha White
Poster
Tue 10:00 Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning
Amin Rakhsha, Goran Radanovic, Rati Devidze, Jerry Zhu, Adish Singla
Poster
Tue 11:00 Domain Adaptive Imitation Learning
Kuno Kim, Yihong Gu, Jiaming Song, Shengjia Zhao, Stefano Ermon
Poster
Tue 12:00 Multi-step Greedy Reinforcement Learning Algorithms
Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh
Poster
Tue 12:00 Learning Portable Representations for High-Level Planning
Steve James, Benjamin Rosman, George Konidaris
Poster
Tue 13:00 Sequential Transfer in Reinforcement Learning with a Generative Model
Andrea Tirinzoni, Riccardo Poiani, Marcello Restelli
Poster
Tue 15:00 Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
Poster
Wed 5:00 What can I do here? A Theory of Affordances in Reinforcement Learning
Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, David Abel, Doina Precup
Poster
Wed 8:00 Learning to Score Behaviors for Guided Policy Optimization
Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Krzysztof Choromanski, Anna Choromanska, Michael Jordan
Poster
Wed 8:00 Identifying the Reward Function by Anchor Actions
Sinong Geng, Houssam Nassif, Charlie Manzanares, Max Reppen, Ronnie Sircar
Poster
Wed 9:00 Accountable Off-Policy Evaluation With Kernel Bellman Statistics
Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu
Poster
Wed 9:00 Flexible and Efficient Long-Range Planning Through Curious Exploration
Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin Feigelis, Daniel Yamins
Poster
Wed 11:00 A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation
Pan Xu, Quanquan Gu
Poster
Wed 11:00 Option Discovery in the Absence of Rewards with Manifold Analysis
Amitay Bar, Ronen Talmon, Ron Meir
Poster
Wed 12:00 No-Regret Exploration in Goal-Oriented Reinforcement Learning
Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric
Poster
Wed 12:00 Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Celi, Emma Brunskill, Finale Doshi-Velez
Poster
Wed 12:00 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation
Marc Abeille, Alessandro Lazaric
Poster
Wed 14:00 Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning
Alberto Maria Metelli, Flavio Mazzolini, Lorenzo Bisi, Luca Sabbioni, Marcello Restelli
Poster
Wed 16:00 Safe Reinforcement Learning in Constrained Markov Decision Processes
Akifumi Wachi, Yanan Sui
Poster
Thu 6:00 Estimating Q(s,s') with Deep Deterministic Dynamics Gradients
Ashley Edwards, Himanshu Sahni, Rosanne Liu, Jane Hung, Ankit Jain, Rui Wang, Adrien Ecoffet, Thomas Miconi, Charles Isbell, Jason Yosinski
Poster
Thu 6:00 Constrained Markov Decision Processes via Backward Value Functions
Harsh Satija, Philip Amortila, Joelle Pineau
Poster
Thu 6:00 Reducing Sampling Error in Batch Temporal Difference Learning
Brahma Pavse, Ishan Durugkar, Josiah Hanna, Peter Stone
Poster
Thu 7:00 Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning
Lingxiao Wang, Zhuoran Yang, Zhaoran Wang
Poster
Thu 7:00 ConQUR: Mitigating Delusional Bias in Deep Q-Learning
DiJia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier
Poster
Thu 8:00 Gradient Temporal-Difference Learning with Regularized Corrections
Sina Ghiassian, Andrew Patterson, Shivam Garg, Dhawal Gupta, Adam White, Martha White
Poster
Thu 8:00 Momentum-Based Policy Gradient Methods
Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
Poster
Thu 9:00 Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions
Michael Chang, Sid Kaushik, S. Matthew Weinberg, Thomas Griffiths, Sergey Levine
Poster
Thu 12:00 Monte-Carlo Tree Search as Regularized Policy Optimization
Jean-Bastien Grill, Florent Altché, Yunhao Tang, Thomas Hubert, Michal Valko, Ioannis Antonoglou, Remi Munos
Poster
Thu 17:00 Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making
Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng