08461 Abstracts Collection -- Planning in Multiagent Systems

From the 9th of November to the 14th of November 2008 the Dagstuhl Seminar 08461 \u27`Planning in Multiagent Systems\u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Opening the PANDORA-BOX: Planning and Executing Timelines in a Training Environment

This paper introduces a novel use of timeline-based planning as the core element within a dynamic training environment designed for crisis managers. Training for crisis decision makers at the strategic level poses a number of challenges that range from the necessity to foster creative decision making to the need for the creation of engaging and realistic scenarios in support of experiential learning. This article describes our efforts to build an end-to-end system, called the PANDORA BOX, that helps the trainer to populate and deliver a continuous 4-5 hours training session encompassing exercises that encourage a group of decision makers to achieve joint decisions. Specifically the emphasis is given to (a) the timeline-based representation as the core component for creating training sessions and unifying different concepts of the PANDORA domain; (b) the combination of planning and execution functionalities required to maintain and dynamically adapt a "lesson plan" on the basis of both trainee-trainer interaction and individual behaviors and performance; (c) the importance of keeping the trainer in close control of the activity loop

Robust optimization over time by learning problem space characteristics

Robust optimization over time is a new way to tackle dynamic optimization problems where the goal is to find solutions that remain acceptable over an extended period of time. The state-of-the-art methods in this domain try to identify robust solutions based on their future predicted fitness values. However, predicting future fitness values is difficult and error prone. In this paper, we propose a new framework based on a multi-population method in which sub-populations are responsible for tracking peaks and also gathering characteristic information about them. When the quality of the current robust solution falls below the acceptance threshold, the algorithm chooses the next robust solution based on the collected information. We propose four different strategies to select the next solution. The experimental results on benchmark problems show that our newly proposed methods perform significantly better than existing algorithms

Enterprise Analysis of Strategic Airlift to Obtain Competitive Advantage through Fuel Efficiency

The rising cost of fuel has led to increasing emphasis on fuel efficiency in the aviation industry. As fuel costs become a larger proportion of total costs, those entities with a dynamic capability to increase their fuel efficiency will obtain competitive advantage. Assessing cargo throughput and fuel efficiency requires the creation of all routes of potential value for a given set of requirements that need to be airlifted from source to destination airfield. The time required for route computation can be significantly reduced through the use of nodal reduction. Use of the proposed model can assist evaluation of enterprise wide efficiency and effectiveness

Heuristic approaches for flight and maintenance planning of large fleets

The nature of military helicopter operations scheduling is such that replanning occurs on a regular basis. With this as a requirement, any solution that takes more than a day to compute is unacceptable. We have shown that this time constraint mitigates against the generation of truly optimum solution using integer programming. Computationally faster, near optimal solutions are a fundamental practical requirement, but the cost of helicopter operations, like that of any aircraft fleet, is large and any sub-optimality will result in substantial cost or operational effectiveness penalties. This research has shown that heuristic, meta-heuristic, and their hybrids can make a computationally difficult problem tractable to the level acceptable for solving real lift problem complexities. The result indicate that the computationally fast approaches developed are inevitable sub-optimal but maintain enough quality to significantly improve upon current approaches to FMP and are practically useful

Planification de mission pour un système de lancement aéroporté autonome

Cette thèse de doctorat s inscrit dans le cadre des activités de recherche sur les systèmes de lancement aéroporté autonome. L originalité du travail est basée sur la planification de mission effectuée par un algorithme de type A*(A-étoile). Cet algorithme a été amélioré pour répondre aux besoins de la mission de largage d un lanceur. Il effectue la planification du chemin le plus court dans un espace tridimensionnel. Le meilleur chemin est choisi à partir de plusieurs points de passage générés dans la région de mission. Une région peut être une phase du vol ou une partie du profil de vol. Le chemin le plus court est identifié par rapport à la présence de différents obstacles dans l espace de recherche et son objectif consiste à atteindre un point désiré. Les obstacles ont différentes dimensions et orientations dans l espace. L étude de leur comportement est associée aux incertitudes en provenance de l environnement. Ils peuvent représenter des régions interdites au vol ou des conditions atmosphériques défavorables. L évolution de ces derniers n est pas prévisible à l avance, ce qui impose l addition d une fonctionnalité dans l algorithme. Il est possible de replanifier le chemin à partir d un point de passage appartenant à un chemin généré en fonction de la position détectée récemment de l obstacle en déplacement pour arriver dans la configuration finale désirée. Cette détection est possible grâce aux capteurs positionnés sur le premier étage de ce système de lancement représenté par un avion-porteur. Les points de passage que le véhicule aérien doit suivre pour atteindre les objectifs importants ne sont pas choisis d une manière aléatoire. Leur génération dans l espace de recherche du chemin est définie en rapport aux limitations dynamiques de l avion. Les modèles cinématique et dynamique du véhicule aérien qui décrivent son évolution sont aussi développés dans cette thèse. Ces modèles sont étudiés dans un système de coordonnées aérodynamiques. Le référentiel traite la présence du vent qui influe sur le comportement du véhicule. Cela nous permet de considérer d une manière prédictive plusieurs incertitudes en provenance de l environnement ou internes pour le véhicule. Les perturbations internes sont provoquées par le largage du lanceur. Le régime transitoire est relié à la perte de masse qui pour certaines missions peut atteindre le tiers de la masse totale du système de lancement. L algorithme de planification traite une autre prévision la possibilité que le largage ne soit pas réalisé. Cela peut arriver dans le cas où une tempête s est installée dans la région de lancement ou il y a plusieurs obstacles dont l évitement risque de consommer trop de carburant et d empêcher le retour sur le site d atterrissage. Les connexions entre les différents points de passage peuvent être souvent brutes et difficiles à réaliser par le véhicule aérien. Pour résoudre cette problématique dans le deuxième module développé sur la génération de trajectoire réalisable, nous utilisons l approche des polynômes de troisième ordre. Ces polynômes par rapport aux autres techniques diminuent le temps du calcul pour générer une trajectoire réalisable entre deux points de passage consécutifs. Le chemin réalisable est facile à suivre par le système. Pour le suivi de la trajectoire, nous avons introduit dans un troisième module la commande par mode glissant. Le principe de cette commande consiste le choix de la surface de commutation entre la trajectoire actuelle suivie par le véhicule et la trajectoire désirée déterminée par l algorithme de planification A-étoile et générée par les polynômes cartésiens de troisième ordre.This Ph.D. thesis deals with the systems of autonomous airborne launch vehicles. The originality of this work is based on the mission planning released by a graph-based A* (A-star) pathfinding algorithm. This algorithm was improved to respond to the specifications of this launching mission. It carries out the planning of the shortest path in a three-dimensional space. The optimal path is selected from the interconnections of several waypoints generated in the mission area. An area can be a specific mission phase or a part of the flight plan. The shortest path is identified according to the presence of various obstacles during the path search and its objective is to reach a desired point in the region. The obstacles have various dimensions and orientations in space. The study of their behavior is associated with disturbances coming from the environment. They could be forbidden flight regions or unfavorable atmospheric conditions. The evolution of the latter cannot be always predicted in advance, which still imposes an improvement that can be added in the operation of the algorithm. The path replanning is also possible. Starting from a safe waypoint from an already generated path according to a recently detected obstacle, a new path can be planned from this point considering the new obstacle coordinates to arrive at the desired final configuration. This detection will be taken into account by the sensors situated on the airborne launcher called a carrier to define the final necessary computing time. The waypoints which the airborne vehicle must follow to achieve the important mission goals are not selected in a random manner. Their generation in the search space is defined according to the dynamic limitations of the vehicle. The kinematic and dynamic models of the carrier are also developed in this thesis. These models are studied in an aerodynamic reference frame. This frame treats the presence of the wind which influences the vehicle evolution in space. That enables to consider in a predictive manner several uncertainties coming from the environment or internal for the vehicle. The internal disturbances are caused by the launching mode relied to a significant loss of mass which for certain missions can reach a half of the total mass of the launching system. The planning algorithm treats in a predictive manner the possibility that the launching is not executed. That can happen if in the launching region a storm is settled or there are several obstacles that avoidance is likely to consume the fuel of the carrier and to prevent the successful return on the landing site. The interconnections between the various waypoints can be often rough and difficult to execute by the airborne launcher. To solve these problems a second module has to be developed to generate a feasible trajectory using the polynomials of third order.. Compared to other techniques this one decreases the calculation time of the trajectory between two consecutive waypoints. The feasible path is easy to follow by the airborne launcher. For the trajectory tracking we introduced into a third module the sliding mode control. The functionality of this control is in the choice of switching surfaces between the current trajectory tracking by the vehicle and the desired trajectory defined by the A* algorithm waypoints and generated by the third order polynomials.EVRY-Bib. électronique (912289901) / SudocSudocFranceF