6,454 research outputs found
Efficient Solution of Language Equations Using Partitioned Representations
A class of discrete event synthesis problems can be reduced to solving
language equations f . X ⊆ S, where F is the fixed component and S the
specification. Sequential synthesis deals with FSMs when the automata for F and
S are prefix closed, and are naturally represented by multi-level networks with
latches. For this special case, we present an efficient computation, using
partitioned representations, of the most general prefix-closed solution of the
above class of language equations. The transition and the output relations of
the FSMs for F and S in their partitioned form are represented by the sets of
output and next state functions of the corresponding networks. Experimentally,
we show that using partitioned representations is much faster than using
monolithic representations, as well as applicable to larger problem instances.Comment: Submitted on behalf of EDAA (http://www.edaa.com/
Optimal path planning for surveillance with temporal-logic constraints
In this paper we present a method for automatically generating optimal robot paths satisfying high-level mission specifications. The motion of the robot in the environment is modeled as a weighted transition system. The mission is specified by an arbitrary linear temporal-logic (LTL) formula over propositions satisfied at the regions of a partitioned environment. The mission specification contains an optimizing proposition, which must be repeatedly satisfied. The cost function that we seek to minimize is the maximum time between satisfying instances of the optimizing proposition. For every environment model, and for every formula, our method computes a robot path that minimizes the cost function. The problem is motivated by applications in robotic monitoring and data-gathering. In this setting, the optimizing proposition is satisfied at all locations where data can be uploaded, and the LTL formula specifies a complex data-collection mission. Our method utilizes Büchi automata to produce an automaton (which can be thought of as a graph) whose runs satisfy the temporal-logic specification. We then present a graph algorithm that computes a run corresponding to the optimal robot path. We present an implementation for a robot performing data collection in a road-network platform.This material is based upon work supported in part by ONR-MURI (award N00014-09-1-1051), ARO (award W911NF-09-1-0088), and Masaryk University (grant numbers LH11065 and GD102/09/H042), and other funding sources (AFOSR YIP FA9550-09-1-0209, NSF CNS-1035588, NSF CNS-0834260). (N00014-09-1-1051 - ONR-MURI; W911NF-09-1-0088 - ARO; LH11065 - Masaryk University; GD102/09/H042 - Masaryk University; FA9550-09-1-0209 - AFOSR YIP; CNS-1035588 - NSF; CNS-0834260 - NSF
It Is NL-complete to Decide Whether a Hairpin Completion of Regular Languages Is Regular
The hairpin completion is an operation on formal languages which is inspired
by the hairpin formation in biochemistry. Hairpin formations occur naturally
within DNA-computing. It has been known that the hairpin completion of a
regular language is linear context-free, but not regular, in general. However,
for some time it is was open whether the regularity of the hairpin completion
of a regular language is is decidable. In 2009 this decidability problem has
been solved positively by providing a polynomial time algorithm. In this paper
we improve the complexity bound by showing that the decision problem is
actually NL-complete. This complexity bound holds for both, the one-sided and
the two-sided hairpin completions
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