Reinforcement Workbench for FreeCAD
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Updated
Sep 16, 2024 - Python
Reinforcement Workbench for FreeCAD
This project serves as a purpose to understand different Reinforcement Learning algorithms, visualize training results, and simulate the testing process.
Solvers for NP-hard and NP-complete problems with an emphasis on high-performance GPU computing.
The task is based on the implementation of Classical RL algorithms on the customized environments such as Frozen lake, Flappy Bird game and on some open ai gym environments such as MiniGrid..
uitb-tools: Data analysis and design tools for the uitb framework.
SEIKO is a novel reinforcement learning method to efficiently fine-tune diffusion models in an online setting. Our methods outperform all baselines (PPO, classifier-based guidance, direct reward backpropagation) for fine-tuning Stable Diffusion.
Kitten Reinforcement add-on for Anki
Flexible, reusable reinforcement learning (Q learning) implementation in Rust
An implementation of a SARSA agent to learn policies in the Frozen Lake environment from OpenAI gym.
Gym environments and agents for autonomous driving.
one key encryptor android classes.dex and repatch apk
🍄Reinforcement Learning: Super Mario Bros with dueling dqn🍄
An attempt to build a chess AI based on Reinforcement learning
A PyTorch Library for Reinforcement Learning Research
Robotic Arm learns to approach objects using Deep Reinforcement Learning
Reinforcement learning is a machine learning technique where agents learn to make optimal decisions by maximizing reward signals through interactions with environment. This repository provides a curated list of resources for learning reinforcement learning, including courses, & tutorials from various providers.
Code for my paper: "Theta sequences as eligibility traces: a biological solution to credit assignment"
A quick reference table for common development and splice lengths of steel reinforcement per ACI 318
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