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mujoco-worldgen

Automatic object XML generation for Mujoco

multi-agent-emergence-environments

Environment generation code for the paper "Emergent Tool Use From Multi-Agent Autocurricula"

multiagent-particle-envs

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

mvtae-multivariate-temporal-autoencoder

This code demonstrates a multi-branch deep neural network approach to tackling the problem of multivariate temporal sequence prediction by modelling a latent state vector representation of data windows through the use of a recurrent autoencoder and predictive model.

navigation-her

2D Gridworld navigation using RL with Hindsight Experience Replay

nfwpo_final_code

noreward-rl

[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning

overthewall

免费翻墙指南

pandas-ta

Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators

policy-gradient

Minimal Monte Carlo Policy Gradient (REINFORCE) Algorithm Implementation in Keras

policy-gradient-and-actor-critic-keras

Simple implementation of Policy Gradient (PG)/ Actor-Critic with keras

ppo

Proximal Policy Optimization implementation with TensorFlow

ppo-keras

My implementation of the Proximal Policy Optisation algorithm using Keras as a backend

ppo-keras-1

Keras Implementation of PPO to solve OpenAI Gym Environments

predictions

pytorch-cspnet

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

pytorch-maddpg

A pytorch implementation of MADDPG (multi-agent deep deterministic policy gradient)

pytorch-sgns

Skipgram Negative Sampling in PyTorch

pytorch_word2vec

Use pytorch to implement word2vec

q-trading-pytorch

DQN stock trading pytorch implementation

qlib

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.

recurrent-neural-network-pricing-model

Price Prediction Case Study predicting the Bitcoin price and the Google stock price using Deep Learning, RNN with LSTM layers with TensorFlow and Keras in Python. (Includes: Data, Case Study Paper, Code)

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

reinforcement-learning-1

Minimal and Clean Reinforcement Learning Examples

reinforcement-learning-2

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

reinforcement-learning-for-time-series-forecasting

Alojamiento del código fuente y datos del proyecto Proyección del comportamiento de enlaces en redes inalámbricas LLN mediante series de tiempo aplicando algoritmos de aprendizaje por refuerzo.

reinforcement-learning-in-portfolio-management-

In this paper, we implement three state-of-art continuous reinforcement learning algorithms, Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO) and Policy Gradient (PG)in portfolio management.

reversi-alpha-zero

Reversi reinforcement learning by AlphaGo Zero methods.

rl-for-financial-time-series-prediction

training a dqn rl algorithm for predicting bitcoin price