Popular GitHub Repositories for Sac Planning

An elegant PyTorch deep reinforcement learning library.

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

Open Source AI coding assistant for planning, building, and fixing code. We're a superset of Roo, Cline, and our own features. Follow us: kilocode.ai/social

A code-first agent framework for seamlessly planning and executing data analytics tasks.

[Tensorflow] High Correlation Data Removing Method for Deep Reinforcement Learning in Obstacle Avoidance and Path Planning

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

[CVPR 2023 Best Paper Award] Planning-oriented Autonomous Driving

Massively Parallel Deep Reinforcement Learning. ?

AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)

[ICML 2024] Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs (RPG)

A comprehensive list of Implicit Representations and NeRF papers relating to Robotics/RL domain, including papers, codes, and related websites

This is a curated list of "Embodied AI or robot with Large Language Models" research. Watch this repository for the latest updates! ?

For deep RL and the future of AI.

The open source Solver AI for Java, Python and Kotlin to optimize scheduling and routing. Solve the vehicle routing problem, employee rostering, task assignment, maintenance scheduling and other planning problems.

Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".