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New planning method achieves 3x lower complexity using optimal-transport smoothing

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new planning method called SecondOrderSmoothCruiser that improves upon existing techniques by incorporating second-order smoothness. This advancement reduces the oracle complexity from \(\\widetilde O(\\varepsilon^{-4})\) to \(\\widetilde O(\\varepsilon^{-3})\) for planning with generative models. The method utilizes an optimal-transport-smoothed Bellman backup, which has a closed form and a Lipschitz Hessian, enabling a more efficient estimation of state values with fewer simulator calls. AI

IMPACT This research could lead to more efficient AI planning algorithms, reducing computational costs for complex tasks.

RANK_REASON The cluster contains a research paper detailing a novel algorithm and its theoretical improvements. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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New planning method achieves 3x lower complexity using optimal-transport smoothing

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The cluster contains a research paper detailing a novel algorithm and its theoretical improvements. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Tuan Dam ·

    Second-Order Smooth Planning with Optimal-Transport Bellman Smoothing

    arXiv:2609.06484v1 Announce Type: cross Abstract: Planning with a generative model aims to estimate the value of a state using as few simulator calls as possible. SmoothCruiser achieves problem-independent complexity $\widetilde O(\varepsilon^{-4})$ by exploiting the smoothness o…

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