Workshop
Deep Reinforcement Learning
Pieter Abbeel · Chelsea Finn · Joelle Pineau · David Silver · Satinder Singh · Coline Devin · Misha Laskin · Kimin Lee · Janarthanan Rajendran · Vivek Veeriah
Fri 11 Dec, 8:30 a.m. PST
In recent years, the use of deep neural networks as function approximators has enabled researchers to extend reinforcement learning techniques to solve increasingly complex control tasks. The emerging field of deep reinforcement learning has led to remarkable empirical results in rich and varied domains like robotics, strategy games, and multiagent interactions. This workshop will bring together researchers working at the intersection of deep learning and reinforcement learning, and it will help interested researchers outside of the field gain a high-level view about the current state of the art and potential directions for future contributions.
Schedule
Fri 8:30 a.m. - 9:00 a.m.
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Invited talk: PierreYves Oudeyer "Machines that invent their own problems: Towards open-ended learning of skills"
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Talk
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SlidesLive Video |
Pierre-Yves Oudeyer 🔗 |
Fri 9:00 a.m. - 9:15 a.m.
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Contributed Talk: Learning Functionally Decomposed Hierarchies for Continuous Control Tasks with Path Planning
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Talk
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SlidesLive Video |
Sammy Christen · Lukas Jendele · Emre Aksan · Otmar Hilliges 🔗 |
Fri 9:15 a.m. - 9:30 a.m.
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Contributed Talk: Maximum Reward Formulation In Reinforcement Learning
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Talk
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SlidesLive Video |
Vijaya Sai Krishna Gottipati · Yashaswi Pathak · Rohan Nuttall · Sahir . · Raviteja Chunduru · Ahmed Touati · Sriram Ganapathi · Matthew Taylor · Sarath Chandar 🔗 |
Fri 9:30 a.m. - 9:45 a.m.
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Contributed Talk: Accelerating Reinforcement Learning with Learned Skill Priors
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Talk
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SlidesLive Video |
Karl Pertsch · Youngwoon Lee · Joseph Lim 🔗 |
Fri 9:45 a.m. - 10:00 a.m.
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Contributed Talk: Asymmetric self-play for automatic goal discovery in robotic manipulation
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Talk
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SlidesLive Video |
16 presentersOpenAI Robotics · Matthias Plappert · Raul Sampedro · Tao Xu · Ilge Akkaya · Vineet Kosaraju · Peter Welinder · Ruben D'Sa · Arthur Petron · Henrique Ponde · Alex Paino · Hyeonwoo Noh Noh · Lilian Weng · Qiming Yuan · Casey Chu · Wojciech Zaremba |
Fri 10:00 a.m. - 10:30 a.m.
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Invited talk: Marc Bellemare "Autonomous navigation of stratospheric balloons using reinforcement learning"
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Talk
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Marc Bellemare 🔗 |
Fri 10:30 a.m. - 11:00 a.m.
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Break
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Fri 11:00 a.m. - 11:30 a.m.
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Invited talk: Peter Stone "Grounded Simulation Learning for Sim2Real with Connections to Off-Policy Reinforcement Learning"
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Talk
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SlidesLive Video |
Peter Stone 🔗 |
Fri 11:30 a.m. - 11:45 a.m.
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Contributed Talk: Mirror Descent Policy Optimization
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Talk
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SlidesLive Video |
Manan Tomar · Lior Shani · Yonathan Efroni · Mohammad Ghavamzadeh 🔗 |
Fri 11:45 a.m. - 12:00 p.m.
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Contributed Talk: Planning from Pixels using Inverse Dynamics Models
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Talk
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SlidesLive Video |
Keiran Paster · Sheila McIlraith · Jimmy Ba 🔗 |
Fri 12:00 p.m. - 12:30 p.m.
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Invited talk: Matt Botvinick "Alchemy: A Benchmark Task Distribution for Meta-Reinforcement Learning Research"
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Talk
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SlidesLive Video |
Matt Botvinick 🔗 |
Fri 12:30 p.m. - 1:30 p.m.
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Poster session 1 ( Poster session ) > link | 🔗 |
Fri 1:30 p.m. - 2:00 p.m.
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Invited talk: Susan Murphy "We used RL but…. Did it work?!"
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Talk
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SlidesLive Video |
Susan Murphy 🔗 |
Fri 2:00 p.m. - 2:15 p.m.
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Contributed Talk: MaxEnt RL and Robust Control
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Talk
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SlidesLive Video |
Benjamin Eysenbach · Sergey Levine 🔗 |
Fri 2:15 p.m. - 2:30 p.m.
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Contributed Talk: Reset-Free Lifelong Learning with Skill-Space Planning
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Talk
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SlidesLive Video |
Kevin Lu · Aditya Grover · Pieter Abbeel · Igor Mordatch 🔗 |
Fri 2:30 p.m. - 3:00 p.m.
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Invited talk: Anusha Nagabandi "Model-based Deep Reinforcement Learning for Robotic Systems"
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Talk
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SlidesLive Video |
Anusha Nagabandi 🔗 |
Fri 3:00 p.m. - 3:30 p.m.
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Break
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Fri 3:30 p.m. - 4:00 p.m.
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Invited talk: Ashley Edwards "Learning Offline from Observation"
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Talk
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SlidesLive Video |
Ashley Edwards 🔗 |
Fri 4:00 p.m. - 4:07 p.m.
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NeurIPS RL Competitions: Flatland challenge
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Talk
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SlidesLive Video |
Sharada Mohanty 🔗 |
Fri 4:07 p.m. - 4:15 p.m.
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NeurIPS RL Competitions: Learning to run a power network
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Talk
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SlidesLive Video |
Antoine Marot 🔗 |
Fri 4:15 p.m. - 4:22 p.m.
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NeurIPS RL Competitions: Procgen challenge
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Talk
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Sharada Mohanty 🔗 |
Fri 4:22 p.m. - 4:30 p.m.
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NeurIPS RL Competitions: MineRL
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Talk
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SlidesLive Video |
William Guss · Stephanie Milani 🔗 |
Fri 4:30 p.m. - 5:00 p.m.
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Invited talk: Karen Liu "Deep Reinforcement Learning for Physical Human-Robot Interaction"
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Talk
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SlidesLive Video |
Karen Liu 🔗 |
Fri 5:00 p.m. - 6:00 p.m.
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Panel discussion
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Pierre-Yves Oudeyer · Marc Bellemare · Peter Stone · Matt Botvinick · Susan Murphy · Anusha Nagabandi · Ashley Edwards · Karen Liu · Pieter Abbeel 🔗 |
Fri 6:00 p.m. - 7:00 p.m.
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Poster session 2 ( Poster session ) > link | 🔗 |
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Poster: Planning from Pixels using Inverse Dynamics Models
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Poster: OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
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Poster: Maximum Reward Formulation In Reinforcement Learning
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Poster: Reset-Free Lifelong Learning with Skill-Space Planning
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Poster: Mirror Descent Policy Optimization
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Poster: MaxEnt RL and Robust Control
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Poster: Learning Functionally Decomposed Hierarchies for Continuous Control Tasks with Path Planning
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Poster: Provably Efficient Policy Optimization via Thompson Sampling
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Poster: Weighted Bellman Backups for Improved Signal-to-Noise in Q-Updates
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Poster: Efficient Competitive Self-Play Policy Optimization
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Poster: Asymmetric self-play for automatic goal discovery in robotic manipulation
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Poster
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Poster: Correcting Momentum in Temporal Difference Learning
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Poster: Decoupling Exploration and Exploitation in Meta-Reinforcement Learning without Sacrifices
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Poster: Diverse Exploration via InfoMax Options
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Poster: Model-Based Meta-Reinforcement Learning for Flight with Suspended Payloads
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Poster: Parrot: Data-driven Behavioral Priors for Reinforcement Learning
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Poster: C-Learning: Horizon-Aware Cumulative Accessibility Estimation
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Poster: Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
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Poster: Data-Efficient Reinforcement Learning with Self-Predictive Representations
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Poster: Accelerating Reinforcement Learning with Learned Skill Priors
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Poster: C-Learning: Learning to Achieve Goals via Recursive Classification
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Poster: Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
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Poster: Learning to Reach Goals via Iterated Supervised Learning
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Poster: Unified View of Inference-based Off-policy RL: Decoupling Algorithmic and Implemental Source of Performance Gaps
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Poster: Learning to Sample with Local and Global Contexts in Experience Replay Buffer
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Poster: Adversarial Environment Generation for Learning to Navigate the Web
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Poster: Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments
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Poster: DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies
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Poster: Discovery of Options via Meta-Gradients
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Poster: GRAC: Self-Guided and Self-Regularized Actor-Critic
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Poster: Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity
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Poster: Deep Bayesian Quadrature Policy Gradient
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Poster: PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards
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Poster: A Policy Gradient Method for Task-Agnostic Exploration
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Poster: Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
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Poster: Skill Transfer via Partially Amortized Hierarchical Planning
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Poster: On Effective Parallelization of Monte Carlo Tree Search
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Poster: Mastering Atari with Discrete World Models
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Poster: Average Reward Reinforcement Learning with Monotonic Policy Improvement
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Poster: Combating False Negatives in Adversarial Imitation Learning
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Poster: Evaluating Agents Without Rewards
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Poster: Learning Latent Landmarks for Generalizable Planning
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Poster: Conservative Safety Critics for Exploration
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Poster: Solving Compositional Reinforcement Learning Problems via Task Reduction
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Poster: Deep Q-Learning with Low Switching Cost
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Poster: Learning to Represent Action Values as a Hypergraph on the Action Vertices
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Poster: Addressing Distribution Shift in Online Reinforcement Learning with Offline Datasets
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Poster: TACTO: A Simulator for Learning Control from Touch Sensing
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Poster: Safe Reinforcement Learning with Natural Language Constraints
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Poster: Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
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Poster: An Examination of Preference-based Reinforcement Learning for Treatment Recommendation
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Poster: Model-based Navigation in Environments with Novel Layouts Using Abstract $n$-D Maps
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Poster: Online Safety Assurance for Deep Reinforcement Learning
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Poster: Lyapunov Barrier Policy Optimization
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Poster: Evolving Reinforcement Learning Algorithms
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Poster: Chaining Behaviors from Data with Model-Free Reinforcement Learning
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Poster: Pairwise Weights for Temporal Credit Assignment
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Poster: Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
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Poster: Understanding Learned Reward Functions
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Poster: Addressing reward bias in Adversarial Imitation Learning with neutral reward functions
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Poster: Reinforcement Learning with Bayesian Classifiers: Efficient Skill Learning from Outcome Examples
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Poster: Decoupling Representation Learning from Reinforcement Learning
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Poster: Model-Based Reinforcement Learning via Latent-Space Collocation
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Poster: A Variational Inference Perspective on Goal-Directed Behavior in Reinforcement Learning
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Poster: SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
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Poster: Predictive PER: Balancing Priority and Diversity towards Stable Deep Reinforcement Learning
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Poster: Latent State Models for Meta-Reinforcement Learning from Images
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Poster: Dream and Search to Control: Latent Space Planning for Continuous Control
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Poster: Explanation Augmented Feedback in Human-in-the-Loop Reinforcement Learning
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Poster: Goal-Conditioned Reinforcement Learning in the Presence of an Adversary
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Poster: Regularized Inverse Reinforcement Learning
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Poster: Domain Adversarial Reinforcement Learning
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Poster: Safety Aware Reinforcement Learning
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Poster: Sample Efficient Training in Multi-Agent AdversarialGames with Limited Teammate Communication
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Poster: Amortized Variational Deep Q Network
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Poster: Disentangled Planning and Control in Vision Based Robotics via Reward Machines
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Poster: Maximum Mutation Reinforcement Learning for Scalable Control
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Poster: Unsupervised Task Clustering for Multi-Task Reinforcement Learning
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Poster: Learning Intrinsic Symbolic Rewards in Reinforcement Learning
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Poster: Preventing Value Function Collapse in Ensemble Q-Learning by Maximizing Representation Diversity
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Poster: Action and Perception as Divergence Minimization
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Poster: Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
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Poster: D2RL: Deep Dense Architectures in Reinforcement Learning
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Poster: Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms
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Poster: Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization
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Poster: What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study
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Poster: Semantic State Representation for Reinforcement Learning
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Poster: Hyperparameter Auto-tuning in Self-Supervised Robotic Learning
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Poster: Targeted Query-based Action-Space Adversarial Policies on Deep Reinforcement Learning Agents
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Poster: Abstract Value Iteration for Hierarchical Deep Reinforcement Learning
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Poster: Compute- and Memory-Efficient Reinforcement Learning with Latent Experience Replay
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Poster: Emergent Road Rules In Multi-Agent Driving Environments
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Poster: An Algorithmic Causal Model of Credit Assignment in Reinforcement Learning
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Poster: Learning to Weight Imperfect Demonstrations
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Poster: Structure and randomness in planning and reinforcement learning
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Poster: Parameter-based Value Functions
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Poster: Influence-aware Memory for Deep Reinforcement Learning in POMDPs
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Poster: Modular Training, Integrated Planning Deep Reinforcement Learning for Mobile Robot Navigation
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Poster: How to make Deep RL work in Practice
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Poster: Super-Human Performance in Gran Turismo Sport Using Deep Reinforcement Learning
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Poster: Which Mutual-Information Representation Learning Objectives are Sufficient for Control?
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Poster: Curriculum Learning through Distilled Discriminators
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Poster: Self-Supervised Policy Adaptation during Deployment
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Poster: Trust, but verify: model-based exploration in sparse reward environments
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Poster: Optimizing Traffic Bottleneck Throughput using Cooperative, Decentralized Autonomous Vehicles
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Poster: Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking
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Poster: Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research
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Poster: Reinforcement Learning with Latent Flow
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Poster: Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
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Poster: AWAC: Accelerating Online Reinforcement Learning With Offline Datasets
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Poster: Inter-Level Cooperation in Hierarchical Reinforcement Learning
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Poster: Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning
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Poster: Multi-Agent Option Critic Architecture
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Poster: Measuring Visual Generalization in Continuous Control from Pixels
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Poster: Policy Learning Using Weak Supervision
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Poster: Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments
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Poster: Unsupervised Domain Adaptation for Visual Navigation
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Poster: Learning Markov State Abstractions for Deep Reinforcement Learning
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Poster: Value Generalization among Policies: Improving Value Function with Policy Representation
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Poster: Energy-based Surprise Minimization for Multi-Agent Value Factorization
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Poster: Backtesting Optimal Trade Execution Policies in Agent-Based Market Simulator
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Poster: Successor Landmarks for Efficient Exploration and Long-Horizon Navigation
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Poster: Multi-task Reinforcement Learning with a Planning Quasi-Metric
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Poster: R-LAtte: Visual Control via Deep Reinforcement Learning with Attention Network
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Poster: Quantifying Differences in Reward Functions
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Poster: DERAIL: Diagnostic Environments for Reward And Imitation Learning
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Poster: Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations
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Poster: Unlocking the Potential of Deep Counterfactual Value Networks
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Poster: FactoredRL: Leveraging Factored Graphs for Deep Reinforcement Learning
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Poster: Reusability and Transferability of Macro Actions for Reinforcement Learning
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Poster: Interactive Visualization for Debugging RL
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Poster: A Deep Value-based Policy Search Approach for Real-world Vehicle Repositioning on Mobility-on-Demand Platforms
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Poster: FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance
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Poster: Visual Imitation with Reinforcement Learning using Recurrent Siamese Networks
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Poster: Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning
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Poster: XLVIN: eXecuted Latent Value Iteration Nets
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Poster: Beyond Exponentially Discounted Sum: Automatic Learning of Return Function
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Poster: XT2: Training an X-to-Text Typing Interface with Online Learning from Implicit Feedback
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Poster: Greedy Multi-Step Off-Policy Reinforcement Learning
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Poster: Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning
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Poster: Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation
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Poster: ReaPER: Improving Sample Efficiency in Model-Based Latent Imagination
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Poster: Model-Based Reinforcement Learning: A Compressed Survey
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Poster: BeBold: Exploration Beyond the Boundary of Explored Regions
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Poster: Model-Based Visual Planning with Self-Supervised Functional Distances
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Poster: Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning
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Poster: Utilizing Skipped Frames in Action Repeats via Pseudo-Actions
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Poster: Bringing order into Actor-Critic Algorithms usingStackelberg Games
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Poster: Continual Model-Based Reinforcement Learning withHypernetworks
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Poster: Online Hyper-parameter Tuning in Off-policy Learning via Evolutionary Strategies
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Poster: Policy Guided Planning in Learned Latent Space
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Poster: PettingZoo: Gym for Multi-Agent Reinforcement Learning
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Poster: DREAM: Deep Regret minimization with Advantage baselines and Model-free learning
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