Search Results for author: Edward A. Lee

Found 4 papers, 1 papers with code

Learning Heuristics for Quantified Boolean Formulas through Deep Reinforcement Learning

1 code implementation • 20 Jul 2018 • Gil Lederman, Markus N. Rabe, Edward A. Lee, Sanjit A. Seshia

We demonstrate how to learn efficient heuristics for automated reasoning algorithms for quantified Boolean formulas through deep reinforcement learning.

reinforcement-learning Reinforcement Learning (RL)

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Learning Heuristics for Automated Reasoning through Reinforcement Learning

no code implementations • ICLR 2019 • Gil Lederman, Markus N. Rabe, Edward A. Lee, Sanjit A. Seshia

We demonstrate how to learn efficient heuristics for automated reasoning algorithms through deep reinforcement learning.

reinforcement-learning Reinforcement Learning (RL)

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Learning Heuristics for Quantified Boolean Formulas through Reinforcement Learning

no code implementations • ICLR 2020 • Gil Lederman, Markus Rabe, Sanjit Seshia, Edward A. Lee

We demonstrate how to learn efficient heuristics for automated reasoning algorithms for quantified Boolean formulas through deep reinforcement learning.

reinforcement-learning Reinforcement Learning (RL)

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Efficient Parallel Reinforcement Learning Framework using the Reactor Model

no code implementations • 7 Dec 2023 • Jacky Kwok, Marten Lohstroh, Edward A. Lee

Parallel Reinforcement Learning (RL) frameworks are essential for mapping RL workloads to multiple computational resources, allowing for faster generation of samples, estimation of values, and policy improvement.

OpenAI Gym Q-Learning +2

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