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The most efficient planning algorithms recently developed are mainly based on Graphplan system or on sat-isfiability approach. In this paper we present a new approach to plan generation based on planning graph analysis, which can be considered as a bridge between the two planning approaches. The method exploits the propagation of planning axioms and(More)
  • Victor Gladun, Adil Timofeev, Larissa Zainutdinova, Alexander Eremeev, Levon Aslanian, Alexander Kleshchev +37 others
  • 2006
IJ ITA is official publisher of the scientific papers of the members of the Association of Developers and Users of Intellectualized Systems (ADUIS). IJ ITA welcomes scientific papers connected with any information theory or its application. Original and non-standard ideas will be published with preferences. IJ ITA rules for preparing the manuscripts are(More)
In this paper a planning framework based on Ant Colony Optimization techniques is presented. It is well known that finding optimal solutions to planning problems is a very hard computational problem. Stochastic methods do not guarantee either optimality or completeness , but it has been proved that in many applications they are able to find very good, often(More)
In this paper an application of the meta–heuristic Ant Colony Optimization to optimal planning is presented. It is well known that finding out optimal solutions to planning problem is a very hard computational problem. Approximate methods do not guarantee either optimality or completeness, but it has been proved that in many applications they are able to(More)
INTRODUCTION AND HYPOTHESIS The objective of this study was to report 1 year anatomical and functional outcomes of trocar-guided total tension-free vaginal mesh (Prolift) repair for post-hysterectomy vaginal vault prolapse with one continuous piece of polypropylene mesh. METHODS We conducted a prospective observational cohort study of 46 patients. A(More)
In this paper a planning framework based on Ant Colony Optimization techniques is presented. Optimal planning is a very hard computational problem which has been coped with different method-ologies. Approximate methods do not guarantee either optimality or completeness, but it has been proved that in many applications they are able to find very good, often(More)
ACOplan is a planner based on the ant colony optimization framework. Using the ACO framework to solve planning optimization problems , one of the main issues to address is the choice of informative and easy to compute pheromone models. In this paper we present and discuss an experimental evaluation of the several pheromone models implemented in ACOPlan. The(More)