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This project explores deep reinforcement learning, hybrid actor-critic approach with A3C/PPO combined with curiosity for playing Super Mario Bros

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sadeqa/Super-Mario-Bros-RL

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Deep Reinforcement Learning : A3C | PPO | Curiosity applied to Super Mario Bros.

This is the final project for the Reinforcement Learning course at the MVA Masters 2018/2019.

The project was done by Amine Sadeq & Otmane Sakhi, You can check the final project paper : ["Exploring Deep Reinforcement Learning with Super Mario Bros"] in this repository.

It explores A3C and PPO algorithms and combine them with an intrinsic reward based on curiosity.

A3C curiosity vs no curiosity in Dense reward

dense_cur

A3C curiosity vs no curiosity in Sparse reward

sparse_cur

A3C curiosity vs PPO curiosity in Dense reward

dense_ppo

A3C curiosity vs PPO curiosity in Sparse reward

sparse_ppo

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This project explores deep reinforcement learning, hybrid actor-critic approach with A3C/PPO combined with curiosity for playing Super Mario Bros

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