RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
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Updated
May 12, 2024 - Python
RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout
Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO
TraderNet-CRv2 - Combining Deep Reinforcement Learning with Technical Analysis and Trend Monitoring on Cryptocurrency Markets
Bayesian Reward Shaping Framework for Deep Reinforcement Learning
Dota 2 bot that is trained by Deep RL with expert demonstrations
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.
Code from the IJCAI 2019 paper "Controllable Neural Story Plot Generation via Reward Shaping"
Guide Your Agent with Adaptive Multimodal Rewards (NeurIPS 2023 Accepted)
Code for NeurIPS 2022 paper Exploiting Reward Shifting in Value-Based Deep RL
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.
BAT Basic Attention Token, Brave, Uphold, DAPP, Cryptocurrenies.
A lightweight package for running small experiments with reward shaping in reinforcement learning.
Reinforcement Learning Exploration of PPO and training methods in Rocket League
Ressources pour la présentation orale: "Une intuition sur RUDDER (Return Decomposition for Delayed Rewards)"
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
Reward shaping library
Benchmarks for risk-aware reward shaping of autonomous driving
Code for "DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks"
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