BillHan-Fantast

BlockchainLab

gym

A toolkit for developing and comparing reinforcement learning algorithms.

HoldEmSimulator

The goal is to simulate games of Texas Hold'em (with no one folding) many times to determine which hands are strongest.

IsaacGymEnvs

Isaac Gym Reinforcement Learning Environments

LSTM-Neural-Network-for-Time-Series-Prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

MAAC

Code for "Actor-Attention-Critic for Multi-Agent Reinforcement Learning" ICML 2019

maddpg

Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

multiagent-particle-envs

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

pymarl

Beta code release for Python Multi-Agent Reinforcement Learning framework

REKCARC-TSC-UHT

清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University

BillHan-Fantast/BlockchainLab

BillHan-Fantast/gym

A toolkit for developing and comparing reinforcement learning algorithms.

BillHan-Fantast/HoldEmSimulator

The goal is to simulate games of Texas Hold'em (with no one folding) many times to determine which hands are strongest.

BillHan-Fantast/IsaacGymEnvs

Isaac Gym Reinforcement Learning Environments

BillHan-Fantast/LSTM-Neural-Network-for-Time-Series-Prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

BillHan-Fantast/MAAC

Code for "Actor-Attention-Critic for Multi-Agent Reinforcement Learning" ICML 2019

BillHan-Fantast/maddpg

Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

BillHan-Fantast/multiagent-particle-envs

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

BillHan-Fantast/pymarl

Beta code release for Python Multi-Agent Reinforcement Learning framework

BillHan-Fantast/REKCARC-TSC-UHT

清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University

BillHan-Fantast/rllab

rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.

BillHan-Fantast/texas-holdem-python

experimenting with simulating games of texas holdem in python