A testing scenario for probabilistic processes

P. Raghavan (Editor), Ling Chueng, Mariëlle Ida Antoinette Stoelinga, Frits Vaandrager

Research output: Contribution to journalArticleAcademicpeer-review

30 Citations (Scopus)

Abstract

We introduce a notion of finite testing, based on statistical hypothesis tests, via a variant of the well-known trace machine. Under this scenario, two processes are deemed observationally equivalent if they cannot be distinguished by any finite test.We consider processes modeled as image finite probabilistic automata and prove that our notion of observational equivalence coincides with the trace distribution equivalence proposed by Segala. Along the way, we give an explicit characterization of the set of probabilistic generalize the Approximation Induction Principle by defining an also prove limit and convex closure properties of trace distributions in an appropriate metric space.
Original languageUndefined
Article number29
Pages (from-to)29:1-29:45
Number of pages45
JournalJournal of the Association for Computing Machinery
Volume54
Issue numberSupplement/6
DOIs
Publication statusPublished - Dec 2007

Keywords

  • EWI-11497
  • IR-58545
  • METIS-245823

Cite this

Raghavan, P. (Editor) ; Chueng, Ling ; Stoelinga, Mariëlle Ida Antoinette ; Vaandrager, Frits. / A testing scenario for probabilistic processes. In: Journal of the Association for Computing Machinery. 2007 ; Vol. 54, No. Supplement/6. pp. 29:1-29:45.
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Raghavan, P (ed.), Chueng, L, Stoelinga, MIA & Vaandrager, F 2007, 'A testing scenario for probabilistic processes' Journal of the Association for Computing Machinery, vol. 54, no. Supplement/6, 29, pp. 29:1-29:45. https://doi.org/10.1145/1314690.1314693

A testing scenario for probabilistic processes. / Raghavan, P. (Editor); Chueng, Ling; Stoelinga, Mariëlle Ida Antoinette; Vaandrager, Frits.

In: Journal of the Association for Computing Machinery, Vol. 54, No. Supplement/6, 29, 12.2007, p. 29:1-29:45.

Research output: Contribution to journalArticleAcademicpeer-review

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T1 - A testing scenario for probabilistic processes

AU - Chueng, Ling

AU - Stoelinga, Mariëlle Ida Antoinette

AU - Vaandrager, Frits

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AB - We introduce a notion of finite testing, based on statistical hypothesis tests, via a variant of the well-known trace machine. Under this scenario, two processes are deemed observationally equivalent if they cannot be distinguished by any finite test.We consider processes modeled as image finite probabilistic automata and prove that our notion of observational equivalence coincides with the trace distribution equivalence proposed by Segala. Along the way, we give an explicit characterization of the set of probabilistic generalize the Approximation Induction Principle by defining an also prove limit and convex closure properties of trace distributions in an appropriate metric space.

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KW - METIS-245823

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