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New robust Q-learning algorithm tackles mean-field control with Wasserstein uncertainty

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new robust Q-learning algorithm designed for mean-field control problems. This algorithm addresses challenges posed by Wasserstein uncertainty in common noise laws by integrating a quantization-and-projection scheme with a Wasserstein dual reformulation. The proposed method has demonstrated convergence and provides finite-time iteration bounds for both synchronous and asynchronous learning schemes, with numerical experiments validating its performance on models related to systemic risk and epidemics. AI

IMPACT Introduces a novel algorithmic approach for reinforcement learning in complex control scenarios.

RANK_REASON The cluster contains an academic paper detailing a new algorithm and its theoretical properties.

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New robust Q-learning algorithm tackles mean-field control with Wasserstein uncertainty

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The cluster contains an academic paper detailing a new algorithm and its theoretical properties.
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COVERAGE [2]

  1. arXiv stat.ML TIER_1 English(EN) · Mathieu Lauri\`ere, Ariel Neufeld, Kyunghyun Park ·

    Robust $Q$-learning for mean-field control under Wasserstein uncertainty in common noise

    arXiv:2606.20356v1 Announce Type: cross Abstract: In this article, we present a robust $Q$-learning algorithm for discrete-time mean-field control problems under Wasserstein uncertainty in the common noise law. The algorithm combines a quantization-and-projection scheme with a Wa…

  2. arXiv stat.ML TIER_1 English(EN) · Kyunghyun Park ·

    Robust $Q$-learning for mean-field control under Wasserstein uncertainty in common noise

    In this article, we present a robust $Q$-learning algorithm for discrete-time mean-field control problems under Wasserstein uncertainty in the common noise law. The algorithm combines a quantization-and-projection scheme with a Wasserstein dual reformulation on the common-noise s…

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