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arXiv · 2305.01521

Unlocking the Power of Representations in Long-term Novelty-based Exploration

Alaa Saade·Steven Kapturowski·Daniele Calandriello·Charles Blundell·Pablo Sprechmann·Leopoldo Sarra·Oliver Groth·Michal Valko·Bilal Piot
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Abstract

We introduce Robust Exploration via Clustering-based Online Density Estimation (RECODE), a non-parametric method for novelty-based exploration that estimates visitation counts for clusters of states based on their similarity in a chosen embedding space. By adapting classical clustering to the nonstationary setting of Deep RL, RECODE can efficiently track state visitation counts over thousands of episodes. We further propose a novel generalization of the inverse dynamics loss, which leverages masked transformer architectures for multi-step prediction; which in conjunction with RECODE achieves a new state-of-the-art in a suite of challenging 3D-exploration tasks in DM-Hard-8. RECODE also sets new state-of-the-art in hard exploration Atari games, and is the first agent to reach the end screen in "Pitfall!".

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Alaa Saade, Steven Kapturowski, Daniele Calandriello, Charles Blundell, Pablo Sprechmann, Leopoldo Sarra, Oliver Groth, Michal Valko, Bilal Piot. 2023-05-02. Unlocking the Power of Representations in Long-term Novelty-based Exploration. https://arxiv.org/abs/2305.01521

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