ω-automaton

About: ω-automaton is a research topic. Over the lifetime, 2299 publications have been published within this topic receiving 68468 citations. The topic is also known as: stream automaton & ω-automata.

The complexity of mean-payoff automaton expression

Abstract: Quantitative languages are extension of Boolean languages that assign to each word a real number. With quantitative languages, systems and specifications can be formalized more accurately. For example, a system may use a varying amount of some resource (e.g., memory consumption, or power consumption) depending on its behavior, and a specification may assign a maximal amount of available resource to each behavior, or fix the long-run average available use of the resource. Mean-payoff automata are finite automata with numerical weights on transitions that assign to each infinite path the long-run average of the transition weights. Mean-payoff automata forms a class of quantitative languages that is not robust, since it is not closed under the basic algebraic operations: min, max, sum and numerical complement. The class of mean-payoff automaton expressions, recently introduced by Chatterjee et al., is currently the only known class of quantitative languages that is robust, expressive and decidable. This class is defined as the closure of mean-payoff automata under the basic algebraic operations. In this work, we prove that all the classical decision problems for mean-payoff expressions are PSPACE-complete. Our proof improves the previously known 4EXPTIME upper bound. In addition, our proof is significantly simpler, and fully accessible to the automata-theoretic community.

Forgetting automata and context-free languages

Abstract: It is shown that context-free languages can be characterized by linear bounded automata with the following restriction: the head can either move right without rewriting or move left with erasing the current cell (i.e. rewriting it with a special, nonrewriteable, symbol). If, instead of erasing, we consider deleting (complete removing of the cell), the corresponding automata are less powerful.

One-Way reversible and quantum finite automata with advice

Abstract: We examine characteristic features of reversible and quantum computations in the presence of supplementary information, known as advice. In particular, we present a simple, algebraic characterization of languages recognized by one-way reversible finite automata with advice. With a further elaborate argument, a similar but slightly weaker result for bounded-error one-way quantum finite automata is also proven. As an immediate application of those features, we demonstrate certain containments and separations among various standard language families that are suitably assisted by advice.