Haoyu Huang's repositories
SNN-Supervised-Learning
Spiking Neural Network for Supervised Learning using PyTorch
ai-economist
Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
cgp
Cartesian Genetic Programming
CMA-ES_Gym
using CMA-ES to train pytorch models for gym environments
Deep-Reinforcement-Learning-Algorithms
27 projects in the framework of Deep Reinforcement Learning algorithms: DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
deep-symbolic-optimization
Source code for deep symbolic optimization.
DPPO
Distributed PPO
easy-rl
强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/
gym-miniworld
Simple 3D interior simulator for RL & robotics research
Izhikevich-simulation
The Python simulation for Izhikevich model using Runge-Kutta Method
Map-Generation
Random Map Generation Project
mlp-mixer-pytorch
An All-MLP solution for Vision, from Google AI
Parallel-CGP
Multiprocess Cartesian Genetic Programming
scikit-opt
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
SNN-CarRacing-SL
train a SNN model using supervised learning to handle CarRacing problem
SNN_arxiv_daily
this repository cord my subscriptions in arxiv with spiking neural network, and [this](https://github.com/shenhaibo123/SNN_summaries) is my summaries.
STBP-simple
A simple direct training implement for SNNs using Spatio-Temporal Backpropagation
Transform2Act
[ICLR 2022 Oral] Official PyTorch Implementation of "Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design".