My blogs and code for machine learning. http://cnblogs.com/pinard

This is the official code for the paper CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning (NeurIPS22).

Reinforcement Learning in Go

GitHub's code repository is all you need

Cheatsheet of Reinforcement Learning (Based on Sutton-Barto Book - 2nd Edition)

Dynamic Attention Encoder-Decoder model to learn and design heuristics to solve capacitated vehicle routing problems

Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, CLIP, ViT, ConvNeXt, SwiftFormer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow.

Long-Term Planning with Deep Reinforcement Learning on Autonomous Drones

Reinforcement Learning material

Reinforcement Learning for Optimal inventory policy

Serpent's Awesome, but, unfortunately, it's too expensive. Let's see what we can do about that

ReLAx - Reinforcement Learning Applications Library

OpenAI Gym wrapper for the Quanser Qube and Quanser Aero

Official implementation of Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Reweighting

docker image for reinforcement learning including Open AI roboschool

Open AI Gym version of Berkeley AI Pacman with images as states

Learning the topic Machine learning, with sample code.

solving a simple 4*4 Gridworld almost similar to openAI gym frozenlake using Monte-Carlo method Reinforcement Learning

Explore foundational AI concepts through the Pac-Man projects, designed for UC Berkeley's CS 188 course. Implement search algorithms, multi-agent strategies, and reinforcement learning techniques in Python, emphasizing real-world applications. Engage in the Eutopia Pac-Man contest for a multiplayer capture-the-flag challenge