Timezone: »
Many advanced Learning from Demonstration (LfD) methods consider the decomposition of complex, real-world tasks into simpler sub-tasks.By reusing the corresponding sub-policies within and between tasks, we can provide training data for each policy from different high-level tasks and compose them to perform novel ones.Existing approaches to modular LfD focus either on learning a single high-level task or depend on domain knowledge and temporal segmentation. In contrast, we propose a weakly supervised, domain-agnostic approach based on task sketches, which include only the sequence of sub-tasks performed in each demonstration. Our approachsimultaneously aligns the sketches with the observed demonstrations and learns the required sub-policies. This improves generalisation in comparison to separate optimisation procedures.We evaluate the approach on multiple domains, including a simulated 3D robot arm control task using purely image-based observations. The results show that our approach performs commensurately with fully supervised approaches, while requiring significantly less annotation effort.
Author Information
Kyriacos Shiarlis (Latent Logic LTD)
Markus Wulfmeier (University of Oxford)
Sasha Salter (University of Oxford)
Shimon Whiteson (University of Oxford)
Ingmar Posner (University of Oxford)
Related Events (a corresponding poster, oral, or spotlight)
-
2018 Poster: TACO: Learning Task Decomposition via Temporal Alignment for Control »
Wed. Jul 11th 04:15 -- 07:00 PM Room Hall B #52
More from the Same Authors
-
2021 : Is Bang-Bang Control All You Need? »
Tim Seyde · Igor Gilitschenski · Wilko Schwarting · Bartolomeo Stellato · Martin Riedmiller · Markus Wulfmeier · Daniela Rus -
2023 : Gromov-Hausdorff Distances for Comparing Product Manifolds of Model Spaces »
Haitz Sáez de Ocáriz Borde · Alvaro Arroyo · Ismael Morales · Ingmar Posner · Xiaowen Dong -
2022 Poster: Communicating via Markov Decision Processes »
Samuel Sokota · Christian Schroeder · Maximilian Igl · Luisa Zintgraf · Phil Torr · Martin Strohmeier · Zico Kolter · Shimon Whiteson · Jakob Foerster -
2022 Spotlight: Communicating via Markov Decision Processes »
Samuel Sokota · Christian Schroeder · Maximilian Igl · Luisa Zintgraf · Phil Torr · Martin Strohmeier · Zico Kolter · Shimon Whiteson · Jakob Foerster -
2022 Poster: Generalized Beliefs for Cooperative AI »
Darius Muglich · Luisa Zintgraf · Christian Schroeder de Witt · Shimon Whiteson · Jakob Foerster -
2022 Spotlight: Generalized Beliefs for Cooperative AI »
Darius Muglich · Luisa Zintgraf · Christian Schroeder de Witt · Shimon Whiteson · Jakob Foerster -
2021 Poster: Average-Reward Off-Policy Policy Evaluation with Function Approximation »
Shangtong Zhang · Yi Wan · Richard Sutton · Shimon Whiteson -
2021 Poster: Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning »
Luisa Zintgraf · Leo Feng · Cong Lu · Maximilian Igl · Kristian Hartikainen · Katja Hofmann · Shimon Whiteson -
2021 Spotlight: Average-Reward Off-Policy Policy Evaluation with Function Approximation »
Shangtong Zhang · Yi Wan · Richard Sutton · Shimon Whiteson -
2021 Spotlight: Breaking the Deadly Triad with a Target Network »
Shangtong Zhang · Hengshuai Yao · Shimon Whiteson -
2021 Spotlight: Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning »
Luisa Zintgraf · Leo Feng · Cong Lu · Maximilian Igl · Kristian Hartikainen · Katja Hofmann · Shimon Whiteson -
2021 Poster: Breaking the Deadly Triad with a Target Network »
Shangtong Zhang · Hengshuai Yao · Shimon Whiteson -
2021 Poster: Data-efficient Hindsight Off-policy Option Learning »
Markus Wulfmeier · Dushyant Rao · Roland Hafner · Thomas Lampe · Abbas Abdolmaleki · Tim Hertweck · Michael Neunert · Dhruva Tirumala Bukkapatnam · Noah Siegel · Nicolas Heess · Martin Riedmiller -
2021 Spotlight: Data-efficient Hindsight Off-policy Option Learning »
Markus Wulfmeier · Dushyant Rao · Roland Hafner · Thomas Lampe · Abbas Abdolmaleki · Tim Hertweck · Michael Neunert · Dhruva Tirumala Bukkapatnam · Noah Siegel · Nicolas Heess · Martin Riedmiller -
2021 Poster: Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning »
Shariq Iqbal · Christian Schroeder · Bei Peng · Wendelin Boehmer · Shimon Whiteson · Fei Sha -
2021 Oral: Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning »
Shariq Iqbal · Christian Schroeder · Bei Peng · Wendelin Boehmer · Shimon Whiteson · Fei Sha -
2021 Poster: Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning »
Anuj Mahajan · Mikayel Samvelyan · Lei Mao · Viktor Makoviychuk · Animesh Garg · Jean Kossaifi · Shimon Whiteson · Yuke Zhu · Anima Anandkumar -
2021 Poster: UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning »
Tarun Gupta · Anuj Mahajan · Bei Peng · Wendelin Boehmer · Shimon Whiteson -
2021 Spotlight: Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning »
Anuj Mahajan · Mikayel Samvelyan · Lei Mao · Viktor Makoviychuk · Animesh Garg · Jean Kossaifi · Shimon Whiteson · Yuke Zhu · Anima Anandkumar -
2021 Spotlight: UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning »
Tarun Gupta · Anuj Mahajan · Bei Peng · Wendelin Boehmer · Shimon Whiteson -
2020 : Panel Discussion 1 »
Daniel Cremers · Nemanja Djuric · Ingmar Posner · Dariu Gavrila -
2020 : Q&A: Ingmar Posner »
Ingmar Posner -
2020 : Invited Talk: Under the Radar: System-Level Self-Supervision for Radar Perception and Navigation (Ingmar Posner) »
Ingmar Posner -
2020 Poster: Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation »
Shangtong Zhang · Bo Liu · Hengshuai Yao · Shimon Whiteson -
2020 Poster: Deep Coordination Graphs »
Wendelin Boehmer · Vitaly Kurin · Shimon Whiteson -
2020 Poster: GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values »
Shangtong Zhang · Bo Liu · Shimon Whiteson -
2019 Workshop: Workshop on AI for autonomous driving »
Anna Choromanska · Larry Jackel · Li Erran Li · Juan Carlos Niebles · Adrien Gaidon · Wei-Lun Chao · Ingmar Posner · Wei-Lun (Harry) Chao -
2019 Poster: Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning »
Jakob Foerster · Francis Song · Edward Hughes · Neil Burch · Iain Dunning · Shimon Whiteson · Matthew Botvinick · Michael Bowling -
2019 Poster: On the Limitations of Representing Functions on Sets »
Edward Wagstaff · Fabian Fuchs · Martin Engelcke · Ingmar Posner · Michael A Osborne -
2019 Oral: Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning »
Jakob Foerster · Francis Song · Edward Hughes · Neil Burch · Iain Dunning · Shimon Whiteson · Matthew Botvinick · Michael Bowling -
2019 Oral: On the Limitations of Representing Functions on Sets »
Edward Wagstaff · Fabian Fuchs · Martin Engelcke · Ingmar Posner · Michael A Osborne -
2019 Poster: A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs »
Jingkai Mao · Jakob Foerster · Tim Rocktäschel · Maruan Al-Shedivat · Gregory Farquhar · Shimon Whiteson -
2019 Poster: Fast Context Adaptation via Meta-Learning »
Luisa Zintgraf · Kyriacos Shiarlis · Vitaly Kurin · Katja Hofmann · Shimon Whiteson -
2019 Oral: A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs »
Jingkai Mao · Jakob Foerster · Tim Rocktäschel · Maruan Al-Shedivat · Gregory Farquhar · Shimon Whiteson -
2019 Oral: Fast Context Adaptation via Meta-Learning »
Luisa Zintgraf · Kyriacos Shiarlis · Vitaly Kurin · Katja Hofmann · Shimon Whiteson -
2019 Poster: Fingerprint Policy Optimisation for Robust Reinforcement Learning »
Supratik Paul · Michael A Osborne · Shimon Whiteson -
2019 Oral: Fingerprint Policy Optimisation for Robust Reinforcement Learning »
Supratik Paul · Michael A Osborne · Shimon Whiteson -
2018 Poster: Fourier Policy Gradients »
Mattie Fellows · Kamil Ciosek · Shimon Whiteson -
2018 Oral: Fourier Policy Gradients »
Mattie Fellows · Kamil Ciosek · Shimon Whiteson -
2018 Poster: QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning »
Tabish Rashid · Mikayel Samvelyan · Christian Schroeder · Gregory Farquhar · Jakob Foerster · Shimon Whiteson -
2018 Poster: Deep Variational Reinforcement Learning for POMDPs »
Maximilian Igl · Luisa Zintgraf · Tuan Anh Le · Frank Wood · Shimon Whiteson -
2018 Oral: Deep Variational Reinforcement Learning for POMDPs »
Maximilian Igl · Luisa Zintgraf · Tuan Anh Le · Frank Wood · Shimon Whiteson -
2018 Oral: QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning »
Tabish Rashid · Mikayel Samvelyan · Christian Schroeder · Gregory Farquhar · Jakob Foerster · Shimon Whiteson -
2018 Poster: DiCE: The Infinitely Differentiable Monte Carlo Estimator »
Jakob Foerster · Gregory Farquhar · Maruan Al-Shedivat · Tim Rocktäschel · Eric Xing · Shimon Whiteson -
2018 Oral: DiCE: The Infinitely Differentiable Monte Carlo Estimator »
Jakob Foerster · Gregory Farquhar · Maruan Al-Shedivat · Tim Rocktäschel · Eric Xing · Shimon Whiteson -
2017 Poster: Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning »
Jakob Foerster · Nantas Nardelli · Gregory Farquhar · Triantafyllos Afouras · Phil Torr · Pushmeet Kohli · Shimon Whiteson -
2017 Talk: Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning »
Jakob Foerster · Nantas Nardelli · Gregory Farquhar · Triantafyllos Afouras · Phil Torr · Pushmeet Kohli · Shimon Whiteson