9 Repositories
Python neurips2021_explicable-reward-design_code Libraries
Code for "Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions"
Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions Codebase for the "Adversarial Motion Priors Make Good Substitutes for Com
Learning Synthetic Environments and Reward Networks for Reinforcement Learning
Learning Synthetic Environments and Reward Networks for Reinforcement Learning We explore meta-learning agent-agnostic neural Synthetic Environments (
A Microsoft reward automator, designed to work headless on a raspberry pi
MsReward A Microsoft reward automator, designed to work headless on a raspberry pi. Tested with a pi 3b+ and a pi 4 2Gb . Using a discord bot to log e
Explicable Reward Design for Reinforcement Learning Agents [NeurIPS'21]
Explicable Reward Design for Reinforcement Learning Agents [NeurIPS'21]
PyTorch implementation for paper StARformer: Transformer with State-Action-Reward Representations.
StARformer This repository contains the PyTorch implementation for our paper titled StARformer: Transformer with State-Action-Reward Representations.
Public implementation of "Learning from Suboptimal Demonstration via Self-Supervised Reward Regression" from CoRL'21
Self-Supervised Reward Regression (SSRR) Codebase for CoRL 2021 paper "Learning from Suboptimal Demonstration via Self-Supervised Reward Regression "
A bot for FaucetCrypto a cryptocurrency faucet. The bot can currently claim PTC ads, main reward and all the shortlinks except exe.io and fc.lc.
A bot for the high paying popular cryptocurrency faucet Faucet Crypto. The bot is built using Python and Selenium, currently it is under active develo
This is the source code of RPG (Reward-Randomized Policy Gradient)
RPG (Reward-Randomized Policy Gradient) Zhenggang Tang*, Chao Yu*, Boyuan Chen, Huazhe Xu, Xiaolong Wang, Fei Fang, Simon Shaolei Du, Yu Wang, Yi Wu (
AWS DeepRacer Free Student Workshop: Run faster by using your custom waypoints
AWS DeepRacer Free Student Workshop: Run faster by using your custom waypoints Reward Function Template for waypoints def reward_function(params):