Engineer-To-Order (ETO) Graph Neural Scheduling (GNS) Project
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Updated
May 25, 2024 - Python
Engineer-To-Order (ETO) Graph Neural Scheduling (GNS) Project
Code for "Optimizing ZX-Diagrams with Deep Reinforcement Learning"
Quantum error correction code AI-discovery with Jax
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
An open source deep learning library for Unity.
A Torch Based RL Framework for Rapid Prototyping of Research Papers
Clean baseline implementation of PPO using an episodic TransformerXL memory
JAX Implementation of Proximal Policy Optimisation Algorithm
Snake game environment integrated with OpenAI Gym. Proximal Policy Optimization (PPO) implementation for training. Visualization of training progress and agent performance. Easy to understand code.
✨ Solve multi_dimensional multiple knapsack problem using state_of_the_art Reinforcement Learning Algorithms and transformers
Reinforcement Learning Agents in .NET
Baseline implementation of recurrent PPO using truncated BPTT
Evaluating the impact of curriculum learning on the training process for an intelligent agent in a video game
Basic 2D car environment trained using reinforcement learning within the Stable Baselines 3 framework
Nokia's classic 'snake' game, written in NumPy and converted into a Gymnasium Environment() for use with gradient-based reinforcement learning algorithms
Minimal implementation of Proximal Policy Optimization (PPO) in PyTorch
Various machine learning implementations and tools
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
🚗 3D web app that combines Proximal Policy Optimization with Three.js, enabling users to directly interact with or train AI models on a virtual racetrack.
A PyTorch library for building deep reinforcement learning agents.
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