No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery
Fuente:
arXiv
Saved in:
| Main Authors: | Rutherford, Alexander, Beukman, Michael, Willi, Timon, Lacerda, Bruno, Hawes, Nick, Foerster, Jakob |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Improving Regret Approximation for Unsupervised Dynamic Environment Generation
by: Mead, Harry, et al.
Published: (2026)
by: Mead, Harry, et al.
Published: (2026)
Refining Minimax Regret for Unsupervised Environment Design
by: Beukman, Michael, et al.
Published: (2024)
by: Beukman, Michael, et al.
Published: (2024)
Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Tasks
by: Matthews, Michael, et al.
Published: (2024)
by: Matthews, Michael, et al.
Published: (2024)
JaxUED: A simple and useable UED library in Jax
by: Coward, Samuel, et al.
Published: (2024)
by: Coward, Samuel, et al.
Published: (2024)
Monte Carlo Tree Search with Boltzmann Exploration
by: Painter, Michael, et al.
Published: (2024)
by: Painter, Michael, et al.
Published: (2024)
A Finite-State Controller Based Offline Solver for Deterministic POMDPs
by: Schutz, Alex, et al.
Published: (2025)
by: Schutz, Alex, et al.
Published: (2025)
Mixture of Experts in a Mixture of RL settings
by: Willi, Timon, et al.
Published: (2024)
by: Willi, Timon, et al.
Published: (2024)
Return Capping: Sample-Efficient CVaR Policy Gradient Optimisation
by: Mead, Harry, et al.
Published: (2025)
by: Mead, Harry, et al.
Published: (2025)
DITTO: Offline Imitation Learning with World Models
by: DeMoss, Branton, et al.
Published: (2023)
by: DeMoss, Branton, et al.
Published: (2023)
Policy-Guided Diffusion
by: Jackson, Matthew Thomas, et al.
Published: (2024)
by: Jackson, Matthew Thomas, et al.
Published: (2024)
JaxWildfire: A GPU-Accelerated Wildfire Simulator for Reinforcement Learning
by: Çakır, Ufuk, et al.
Published: (2025)
by: Çakır, Ufuk, et al.
Published: (2025)
HyperVLA: Efficient Inference in Vision-Language-Action Models via Hypernetworks
by: Xiong, Zheng, et al.
Published: (2025)
by: Xiong, Zheng, et al.
Published: (2025)
A Clean Slate for Offline Reinforcement Learning
by: Jackson, Matthew Thomas, et al.
Published: (2025)
by: Jackson, Matthew Thomas, et al.
Published: (2025)
A Transparency Paradox? Investigating the Impact of Explanation Specificity and Autonomous Vehicle Perceptual Inaccuracies on Passengers
by: Omeiza, Daniel, et al.
Published: (2024)
by: Omeiza, Daniel, et al.
Published: (2024)
Efficient Skill Discovery via Regret-Aware Optimization
by: Zhang, He, et al.
Published: (2025)
by: Zhang, He, et al.
Published: (2025)
Regret-Based Federated Causal Discovery with Unknown Interventions
by: Baldo, Federico, et al.
Published: (2025)
by: Baldo, Federico, et al.
Published: (2025)
Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning
by: Schutz, Alex, et al.
Published: (2025)
by: Schutz, Alex, et al.
Published: (2025)
Goal-Conditioned Agents that Learn Everything All at Once
by: Matthews, Michael, et al.
Published: (2026)
by: Matthews, Michael, et al.
Published: (2026)
Reasoning without Regret
by: Chitra, Tarun
Published: (2025)
by: Chitra, Tarun
Published: (2025)
TRACED: Transition-aware Regret Approximation with Co-learnability for Environment Design
by: Cho, Geonwoo, et al.
Published: (2025)
by: Cho, Geonwoo, et al.
Published: (2025)
Analysing the Sample Complexity of Opponent Shaping
by: Fung, Kitty, et al.
Published: (2024)
by: Fung, Kitty, et al.
Published: (2024)
FOSSIL: Regret-Minimizing Curriculum Learning for Metadata-Free and Low-Data Mpox Diagnosis
by: Han, Sahng-Min, et al.
Published: (2025)
by: Han, Sahng-Min, et al.
Published: (2025)
JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
by: Rutherford, Alexander, et al.
Published: (2023)
by: Rutherford, Alexander, et al.
Published: (2023)
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning
by: Moradipari, Ahmadreza, et al.
Published: (2023)
by: Moradipari, Ahmadreza, et al.
Published: (2023)
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
by: Vakili, Sattar, et al.
Published: (2024)
by: Vakili, Sattar, et al.
Published: (2024)
Curriculum Is More Influential Than Haptic Information During Reinforcement Learning of Object Manipulation Against Gravity
by: Ojaghi, Pegah, et al.
Published: (2024)
by: Ojaghi, Pegah, et al.
Published: (2024)
Agentic Skill Discovery
by: Zhao, Xufeng, et al.
Published: (2024)
by: Zhao, Xufeng, et al.
Published: (2024)
No-Regret Reinforcement Learning in Smooth MDPs
by: Maran, Davide, et al.
Published: (2024)
by: Maran, Davide, et al.
Published: (2024)
Eurekaverse: Environment Curriculum Generation via Large Language Models
by: Liang, William, et al.
Published: (2024)
by: Liang, William, et al.
Published: (2024)
The Decrypto Benchmark for Multi-Agent Reasoning and Theory of Mind
by: Lupu, Andrei, et al.
Published: (2025)
by: Lupu, Andrei, et al.
Published: (2025)
Beyond Features: How Dataset Design Influences Multi-Agent Trajectory Prediction Performance
by: Demmler, Tobias, et al.
Published: (2025)
by: Demmler, Tobias, et al.
Published: (2025)
Mixtures of Experts Unlock Parameter Scaling for Deep RL
by: Obando-Ceron, Johan, et al.
Published: (2024)
by: Obando-Ceron, Johan, et al.
Published: (2024)
Identifying Selections for Unsupervised Subtask Discovery
by: Qiu, Yiwen, et al.
Published: (2024)
by: Qiu, Yiwen, et al.
Published: (2024)
Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning
by: Tao, Stone, et al.
Published: (2024)
by: Tao, Stone, et al.
Published: (2024)
CuRLA: Curriculum Learning Based Deep Reinforcement Learning for Autonomous Driving
by: Uppuluri, Bhargava, et al.
Published: (2025)
by: Uppuluri, Bhargava, et al.
Published: (2025)
AutoLoop: Fast Visual SLAM Fine-tuning through Agentic Curriculum Learning
by: Lahiany, Assaf, et al.
Published: (2025)
by: Lahiany, Assaf, et al.
Published: (2025)
Regret-Free Reinforcement Learning for LTL Specifications
by: Majumdar, Rupak, et al.
Published: (2024)
by: Majumdar, Rupak, et al.
Published: (2024)
Regret-Based Defense in Adversarial Reinforcement Learning
by: Belaire, Roman, et al.
Published: (2023)
by: Belaire, Roman, et al.
Published: (2023)
A Regret Perspective on Online Multiple Testing
by: Hao, Qingyang, et al.
Published: (2026)
by: Hao, Qingyang, et al.
Published: (2026)
Human-Aware Robot Navigation via Reinforcement Learning with Hindsight Experience Replay and Curriculum Learning
by: Li, Keyu, et al.
Published: (2021)
by: Li, Keyu, et al.
Published: (2021)
Similar Items
-
Improving Regret Approximation for Unsupervised Dynamic Environment Generation
by: Mead, Harry, et al.
Published: (2026) -
Refining Minimax Regret for Unsupervised Environment Design
by: Beukman, Michael, et al.
Published: (2024) -
Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Tasks
by: Matthews, Michael, et al.
Published: (2024) -
JaxUED: A simple and useable UED library in Jax
by: Coward, Samuel, et al.
Published: (2024) -
Monte Carlo Tree Search with Boltzmann Exploration
by: Painter, Michael, et al.
Published: (2024)