Convex language semantics for nondeterministic probabilistic automata

被引：0
|
作者：
van Heerdt, Gerco [1 ]
Hsu, Justin [2 ]
Ouaknine, Joel [3 ,4 ]
Silva, Alexandra [2 ]
机构：
[1] Droit Financial Technol, London, England
[2] Cornell Univ, Ithaca, NY USA
[3] MPI SWS, Saarbrucken, Germany
[4] Keble Coll, Oxford, England
来源：
THEORETICAL COMPUTER SCIENCE | 2025年 / 1040卷
基金：
英国工程与自然科学研究理事会;
关键词：
D O I：
10.1016/j.tcs.2025.115191
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
We explore language semantics for automata combining probabilistic and nondeterministic behaviors. We first show that there are precisely two natural semantics for probabilistic automata with nondeterminism. For both choices, we show that these automata are strictly more expressive than deterministic probabilistic automata, and we prove that the problem of checking language equivalence is undecidable by reduction from the threshold problem. However, we provide a discounted metric that can be computed to arbitrarily high precision.
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页数：21
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