MuJoCo Games

6 papers with code • 17 benchmarks • 1 datasets

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Most implemented papers

IQ-Learn: Inverse soft-Q Learning for Imitation

Div99/IQ-Learn 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.

A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games

deepmind/open_spiel 12 Jun 2022

This work studies an algorithm, which we call magnetic mirror descent, that is inspired by mirror descent and the non-Euclidean proximal gradient algorithm.

RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning

deepmind/deepmind-research 24 Jun 2020

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.

Weak Human Preference Supervision For Deep Reinforcement Learning

kaichiuwong/rlhps 25 Jul 2020

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.

EDGE: Explaining Deep Reinforcement Learning Policies

henrygwb/edge NeurIPS 2021

With the rapid development of deep reinforcement learning (DRL) techniques, there is an increasing need to understand and interpret DRL policies.

LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning

robfiras/ls-iq 1 Mar 2023

Recent methods for imitation learning directly learn a $Q$-function using an implicit reward formulation rather than an explicit reward function.