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Home Authors Posts by Adrien Ecoffet

Adrien Ecoffet

1 BLOG ARTICLES 2 RESEARCH PAPERS
Adrien Ecoffet is a research scientist with Uber AI Labs.

Engineering Blog Articles

Montezuma’s Revenge Solved by Go-Explore, a New Algorithm for Hard-Exploration Problems (Sets Records on Pitfall, Too)

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Kenneth O. Stanley and Jeff Clune were co-senior authors.

 

In deep reinforcement learning (RL), solving the Atari games Montezuma’s Revenge and Pitfall has been a grand challenge. These games represent a broad class of challenging, real-world problems called

Research Papers

Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients

A. Edwards, Himanshu Sahni, R. Liu, J. Hung, A. Jain, R. Wang, A. Ecoffet, T. Miconi, C. Isbell, J. Yosinski
In this paper, we introduce a novel form of value function, Q(s,s′), that expresses the utility of transitioning from a state s to a neighboring state s′ and then acting optimally thereafter. In order to derive an optimal policy, we develop a forward dynamics model that learns to make next-state predictions that maximize this value. [...] [PDF]
International Conference on Machine Learning (ICML), 2020

Go-Explore: a New Approach for Hard-Exploration Problems

A. Ecoffet, J. Huizinga, J. Lehman, K. Stanley, J. Clune
A grand challenge in reinforcement learning is intelligent exploration, especially when rewards are sparse or deceptive. Two Atari games serve as benchmarks for such hard-exploration domains: Montezuma's Revenge and Pitfall. On both games, current RL algorithms perform poorly, even those with intrinsic motivation, which is the dominant method to improve performance on hard-exploration domains. [...] [PDF]
2019

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