reward-shaping

salesforce/MultiHopKG

Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout

lcswillems/torch-ac

Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO

csmile-1006/ARP

Guide Your Agent with Adaptive Multimodal Rewards (NeurIPS 2023 Accepted)

niksaz/dota2-expert-demo

Dota 2 bot that is trained by Deep RL with expert demonstrations

yining043/NeuOpt

This repo implements our paper, "Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt", which has been accepted at NeurIPS 2023.

kochlisGit/TraderNet-CRv2

TraderNet-CRv2 - Combining Deep Reinforcement Learning with Technical Analysis and Trend Monitoring on Cryptocurrency Markets

holarissun/RewardShifting

Code for NeurIPS 2022 paper Exploiting Reward Shifting in Value-Based Deep RL

mike-gimelfarb/bayesian-reward-shaping

Bayesian Reward Shaping Framework for Deep Reinforcement Learning

awilliea/Risk-based_RL_for_Optimal_Trading_Execution

jbakams/slimebot-volleyball

3D gym environments to train RL agents to play the Slime Volleyball game in 3 dimensions using Webots as simulator.

tongzhoumu/DrS

Code for "DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks"

takato86/shaper

Reward shaping library

zhang-zengjie/Reward4Driving

Benchmarks for risk-aware reward shaping of autonomous driving

dylwil3/reward-shaping

A lightweight package for running small experiments with reward shaping in reinforcement learning.

PoldervaartS/RLRLGym

Reinforcement Learning Exploration of PPO and training methods in Rocket League

CAmayoral/hello-world

BAT Basic Attention Token, Brave, Uphold, DAPP, Cryptocurrenies.

IngyN/macsrl

Project for a semi-centralized logic-based MARL reward shaping method that is scalable in the number of agents and evaluates it in multiple scenarios

lara-martin/StoryPlot-RewardShaping

Code from the IJCAI 2019 paper "Controllable Neural Story Plot Generation via Reward Shaping"

RedLeader962/Une-intuition-sur-RUDDER

Ressources pour la présentation orale: "Une intuition sur RUDDER (Return Decomposition for Delayed Rewards)"

brianwade1/Gym_QLearning_and_RewardShaping

This repo demonstrates basic Q-learning for the Mountain Car Gym environment. It also shows how reward shaping can result in faster training of the agent.

ChiragRadhakrishna43-7/Pacman_MultiAgents

Pacman games with multi agents. Evaluating the performance of Pacman and the ghosts.