22
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Nested Weighted Limit-Average Automata of Bounded Width

      Preprint
      , ,

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          While weighted automata provide a natural framework to express quantitative properties, many basic properties like average response time cannot be expressed with weighted automata. Nested weighted automata extend weighted automata and consist of a master automaton and a set of slave automata that are invoked by the master automaton. Nested weighted automata are strictly more expressive than weighted automata (e.g., average response time can be expressed with nested weighted automata), but the basic decision questions have higher complexity (e.g., for deterministic automata, the emptiness question for nested weighted automata is PSPACE-hard, whereas the corresponding complexity for weighted automata is PTIME). We consider a natural subclass of nested weighted automata where at any point at most a bounded number k of slave automata can be active. We focus on automata whose master value function is the limit average. We show that these nested weighted automata with bounded width are strictly more expressive than weighted automata (e.g., average response time with no overlapping requests can be expressed with bound k=1, but not with non-nested weighted automata). We show that the complexity of the basic decision problems (i.e., emptiness and universality) for the subclass with k constant matches the complexity for weighted automata. Moreover, when k is part of the input given in unary we establish PSPACE-completeness.

          Related collections

          Most cited references10

          • Record: found
          • Abstract: not found
          • Book Chapter: not found

          Markov Decision Processes with Multiple Objectives

            Bookmark
            • Record: found
            • Abstract: not found
            • Book Chapter: not found

            Discounting in LTL

              Bookmark
              • Record: found
              • Abstract: not found
              • Book Chapter: not found

              Markov Decision Processes with Multiple Long-Run Average Objectives

                Bookmark

                Author and article information

                Journal
                2016-06-11
                Article
                1606.03598
                b968ea43-6b99-4aaf-af52-c9b624a66ba0

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                A conference version will appear in MFCS 2016. arXiv admin note: text overlap with arXiv:1604.06764
                cs.FL cs.LO

                Theoretical computer science
                Theoretical computer science

                Comments

                Comment on this article