Accompanying code for a paper
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Updated
Dec 19, 2019 - Python
Accompanying code for a paper
pytorch implementation of SAC, TD3 and TD7 with Mujoco Benchmark results from 4 seeds.
Contextual MDPs with changing rewards and dynamics, implemented based on DeepMind Control Suite
Integrated simulator and hardware controller package for UR3 manipulator
MLPro: Integration Multi-Joint dynamics with Contact (MuJoCo)
In this project, I attempt to solve fetch and slide open gym environment with Hindsight Experience Replay and the I experiment with Prioritised experience replay to see if there are any performance improvements
A Gymnasium benchmark suite for evaluating the robustness and multi-task performance of reinforcement learning algorithms in various discrete and continuous environments.
Official repository of the iMuJoCo (iMitation MuJoCo) dataset
Reinforcement learning environments for planar robotics based on MuJoCo
An agent that manipulates elastic objects using the UR5 robot.
Non-modular implementation of common RL algorithms
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
CSCI-SHU 375 Reinforcement Learning | Fall2020 | Final Project
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