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Classification Under Uncertainty

Authors Orna Kupferman , Ofer Leshkowitz

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LIPIcs.CONCUR.2026.40.pdf
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Subject Classification

ACM Subject Classification
  • Theory of computation
Keywords
  • Formal methods
  • Automata
  • Incomplete Information

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Abstract

Consider a fixed number of disjoint regular languages L_1,…,L_k ⊆ Σ^*. A classifier for L_1,…,L_k is a transducer that receives each moment t in time an input letter σ_t ∈ Σ and outputs an index in {1,…,k} such that if the word σ_1 ⋯ σ_t, generated so far, is in some (unique) language L_i, then this index is i. Classifiers arise naturally in runtime monitoring and online stream processing, where a system must continuously determine which of several specifications or behaviors is currently being realized. The problem of generating classifiers of minimal size has been well studied.
In many applications, the input alphabet is of the form 2^P, for a finite set P of signals. There, the complexity of classification stems not only from the languages but also from the presence of uncertainty, namely when the valuation to some signals may not be known. We introduce and study classification under uncertainty, where the input words may be partially observed. We consider three sources for uncertainty: (1) Given: the input to the problem specifies which signals may be sensed after each behavior. (2) Privacy: the input includes a list of secret behaviors, and the classifier should restrict sensing so that secrets are not revealed. (3) Budget: Sensing of signals incurs a cost, which the classifier should minimize.

Cite As Get BibTex

Orna Kupferman and Ofer Leshkowitz. Classification Under Uncertainty. In 37th International Conference on Concurrency Theory (CONCUR 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 391, pp. 40:1-40:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.CONCUR.2026.40

Author Details

Orna Kupferman
  • School of Computer Science and Engineering, The Hebrew University, Jerusalem, Israel
Ofer Leshkowitz
  • School of Computer Science and Engineering, The Hebrew University, Jerusalem, Israel

Funding

Research supported by the Israel Science Foundation, Grant 3177/25, and European Research Council, Advanced Grant ADVANSYNT.

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