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09/19/2023
Monte-Carlo tree search with uncertainty propagation via optimal transport
This paper introduces a novel backup strategy for Monte-Carlo Tree Searc...
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09/05/2023
Sparse Function-space Representation of Neural Networks
Deep neural networks (NNs) are known to lack uncertainty estimates and s...
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09/01/2023
Suicidal Pedestrian: Generation of Safety-Critical Scenarios for Autonomous Vehicles
Developing reliable autonomous driving algorithms poses challenges in te...
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06/15/2023
Simplified Temporal Consistency Reinforcement Learning
Reinforcement learning is able to solve complex sequential decision-maki...
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03/05/2023
Seq2Seq Imitation Learning for Tactile Feedback-based Manipulation
Robot control for tactile feedback-based manipulation can be difficult d...
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02/17/2023
Swapped goal-conditioned offline reinforcement learning
Offline goal-conditioned reinforcement learning (GCRL) can be challengin...
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02/15/2023
Prioritized offline Goal-swapping Experience Replay
In goal-conditioned offline reinforcement learning, an agent learns from...
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01/30/2023
Hierarchical Imitation Learning with Vector Quantized Models
The ability to plan actions on multiple levels of abstraction enables in...
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11/14/2022
Redeeming Intrinsic Rewards via Constrained Optimization
State-of-the-art reinforcement learning (RL) algorithms typically use ra...
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10/25/2022
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
Offline reinforcement learning, by learning from a fixed dataset, makes ...
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10/04/2022
Continuous Monte Carlo Graph Search
In many complex sequential decision making tasks, online planning is cru...
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09/21/2022
Partially Observable Markov Decision Processes in Robotics: A Survey
Noisy sensing, imperfect control, and environment changes are defining c...
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05/20/2022
Self-Paced Multi-Agent Reinforcement Learning
Curriculum reinforcement learning (CRL) aims to speed up learning of a t...
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03/29/2022
Topological Experience Replay
State-of-the-art deep Q-learning methods update Q-values using state tra...
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02/28/2022
GPU-Accelerated Policy Optimization via Batch Automatic Differentiation of Gaussian Processes for Real-World Control
The ability of Gaussian processes (GPs) to predict the behavior of dynam...
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02/11/2022
A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search
Monte-Carlo Tree Search (MCTS) is a class of methods for solving complex...
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01/24/2022
Adversarially Guided Subgoal Generation for Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (HRL) proposes to solve difficult ta...
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04/22/2021
Reinforcement Learning using Guided Observability
Due to recent breakthroughs, reinforcement learning (RL) has demonstrate...
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03/23/2021
Neural Network Controller for Autonomous Pile Loading Revised
We have recently proposed two pile loading controllers that learn from h...
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02/25/2021
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning
Across machine learning, the use of curricula has shown strong empirical...
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10/26/2020
POMDP Manipulation Planning under Object Composition Uncertainty
Manipulating unknown objects in a cluttered environment is difficult bec...
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09/04/2020
Technical Report: The Policy Graph Improvement Algorithm
Optimizing a partially observable Markov decision process (POMDP) policy...
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07/04/2020
Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization
3D scene models are useful in robotics for tasks such as path planning, ...
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07/01/2020
Convex Regularization in Monte-Carlo Tree Search
Monte-Carlo planning and Reinforcement Learning (RL) are essential to se...
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04/27/2020
Machine Learning Based Mobile Network Throughput Classification
Identifying mobile network problems in 4G cells is more challenging when...
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04/24/2020
Self-Paced Deep Reinforcement Learning
Generalization and reuse of agent behaviour across a variety of learning...
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03/08/2020
Deep Adversarial Reinforcement Learning for Object Disentangling
Deep learning in combination with improved training techniques and high ...
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02/26/2020
Probabilistic approach to physical object disentangling
Physically disentangling entangled objects from each other is a problem ...
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01/01/2020
Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning
Reinforcement learning with sparse rewards is still an open challenge. C...
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11/01/2019
Generalized Mean Estimation in Monte-Carlo Tree Search
We consider Monte-Carlo Tree Search (MCTS) applied to Markov Decision Pr...
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08/15/2019
Model-based Lookahead Reinforcement Learning
Model-based Reinforcement Learning (MBRL) allows data-efficient learning...
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02/26/2019
Information Gathering in Decentralized POMDPs by Policy Graph Improvement
Decentralized policies for information gathering are required when multi...
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02/07/2019
Compatible Natural Gradient Policy Search
Trust-region methods have yielded state-of-the-art results in policy sea...
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11/16/2018