Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM)

🎮 [IJCAI'20][ICLR'19 Workshop] Flow-based Intrinsic Curiosity Module. Playing SuperMario with RL agent and FICM!

Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.

Pytorch implementation of intrinsic curiosity module with proximal policy optimization

Attention-based Curiosity-driven Exploration in Deep Reinforcement Learning

Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM) on Pyramid env, Unity ML

Pytorch based library containing reinforcement learning agents with forward models and intrinsic motivation modules

Master's thesis on model-based intrinsically motivated reinforcement learning in robotic control

Implementations for RL agents that seek to learn about their environment by predicting multiple signals from a single stream of experience.

Implemented DQN with Intrinsic Curiosity Module for a VizDoom competition at nate.

A collection of my implemented advanced & complex RL agents for games like Soccer, Street Fighter, Mortal Kombat, Rubik's Cube, Vizdoom, Montezuma, Kungfu-master, Super-Mario-bros, HalfCheetah and more by implementing advanced DRL concepts like decision transformers, RND, MARL, A3C, ICM & sample_factory. To see my other rl agents please visit