Probabilistic Strategy Logic

Benjamin Aminof, Marta Kwiatkowska, Bastien Maubert, Aniello Murano, Sasha Rubin

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

We introduce Probabilistic Strategy Logic, an extension of Strategy Logic for stochastic systems. The logic has probabilistic terms that allow it to express many standard solution concepts, such as Nash equilibria in randomised strategies, as well as constraints on probabilities, such as independence. We study the model-checking problem for agents with perfect- and imperfect-recall. The former is undecidable, while the latter is decidable in space exponential in the system and triple-exponential in the formula. We identify a natural fragment of the logic, in which every temporal operator is immediately preceded by a probabilistic operator, and show that it is decidable in space exponential in the system and the formula, and double-exponential in the nesting depth of the probabilistic terms. Taking a fixed nesting depth, this gives a fragment that still captures many standard solution concepts, and is decidable in exponential space.
Original languageEnglish
Title of host publicationProceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, (IJCAI) 2019
Editors IJCAI
Pages32-38
Number of pages7
ISBN (Electronic)9780999241141
DOIs
Publication statusPublished - 2019

Publication series

NameProceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence 2019

Fields of science

  • 102 Computer Sciences
  • 102001 Artificial intelligence
  • 102011 Formal languages
  • 102022 Software development
  • 102031 Theoretical computer science
  • 603109 Logic
  • 202006 Computer hardware

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