MuJoCo Games
6 papers with code • 17 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in MuJoCo Games
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MO-Gymnasium
Latest papers
LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning
robfiras/ls-iq
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Recent methods for imitation learning directly learn a $Q$-function using an implicit reward formulation rather than an explicit reward function.
A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games
This work studies an algorithm, which we call magnetic mirror descent, that is inspired by mirror descent and the non-Euclidean proximal gradient algorithm.
EDGE: Explaining Deep Reinforcement Learning Policies
henrygwb/edge
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NeurIPS 2021
With the rapid development of deep reinforcement learning (DRL) techniques, there is an increasing need to understand and interpret DRL policies.
IQ-Learn: Inverse soft-Q Learning for Imitation
Div99/IQ-Learn
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NeurIPS 2021
In many sequential decision-making problems (e. g., robotics control, game playing, sequential prediction), human or expert data is available containing useful information about the task.
Weak Human Preference Supervision For Deep Reinforcement Learning
The current reward learning from human preferences could be used to resolve complex reinforcement learning (RL) tasks without access to a reward function by defining a single fixed preference between pairs of trajectory segments.
RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning
deepmind/deepmind-research
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We hope that our suite of benchmarks will increase the reproducibility of experiments and make it possible to study challenging tasks with a limited computational budget, thus making RL research both more systematic and more accessible across the community.
