mlsanityData to 7 Oct 2026

Online Nonstochastic Control with Adversarial and Static Constraints

arXiv 2302.02426 ↗First posted 5 Feb 2023cs.LG cs.SY eess.SYcited by 5

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Abstract (arXiv)

This paper studies online nonstochastic control problems with adversarial and static constraints. We propose online nonstochastic control algorithms that achieve both sublinear regret and sublinear adversarial constraint violation while keeping static constraint violation minimal against the optimal constrained linear control policy in hindsight. To establish the results, we introduce an online convex optimization with memory framework under adversarial and static constraints, which serves as a subroutine for the constrained online nonstochastic control algorithms. This subroutine also achieves the state-of-the-art regret and constraint violation bounds for constrained online convex optimization problems, which is of independent interest. Our experiments demonstrate the proposed control algorithms are adaptive to adversarial constraints and achieve smaller cumulative costs and violations. Moreover, our algorithms are less conservative and achieve significantly smaller cumulative costs than the state-of-the-art algorithm.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 39 of its 56 references that are in the map. First posted on arXiv 5 Feb 2023.

Builds on

39 of 56 references.

References · 39

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27 more
  1. 2021Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPscited by 78
  2. 2017Online Convex Optimization with Time-Varying Constraintscited by 55
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  7. 2021Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraintscited by 38
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 2; 2025: 0; 2026: 1.

5 papers.

  1. 2023Learning the Uncertainty Sets for Control Dynamics via Set Membership: A Non-Asymptotic Analysiscited by 6
  2. 2023Adaptive Online Non-stochastic Controlcited by 3
  3. 2024Optimistic Online Non-stochastic Control via FTRLcited by 3
  4. 2024Safe and Efficient Online Convex Optimization with Linear Budget Constraints and Partial Feedbackcited by 0
  5. 2026Constrained Online Convex Optimization with Memory and Predictionscited by 0