Code from the IJCAI 2019 paper "Controllable Neural Story Plot Generation via Reward Shaping"
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Updated
May 31, 2022 - Python
Code from the IJCAI 2019 paper "Controllable Neural Story Plot Generation via Reward Shaping"
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.
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
Pacman games with multi agents. Evaluating the performance of Pacman and the ghosts.
A lightweight package for running small experiments with reward shaping in reinforcement learning.
Reinforcement Learning Exploration of PPO and training methods in Rocket League
Reward shaping library
Benchmarks for risk-aware reward shaping of autonomous driving
Code for "DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks"
3D gym environments to train RL agents to play the Slime Volleyball game in 3 dimensions using Webots as simulator.
Bayesian Reward Shaping Framework for Deep Reinforcement Learning
Code for NeurIPS 2022 paper Exploiting Reward Shifting in Value-Based Deep RL
TraderNet-CRv2 - Combining Deep Reinforcement Learning with Technical Analysis and Trend Monitoring on Cryptocurrency Markets
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.
Dota 2 bot that is trained by Deep RL with expert demonstrations
Guide Your Agent with Adaptive Multimodal Rewards (NeurIPS 2023 Accepted)
Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO
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