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Künstliche Intelligenz 27(3) - August 2013

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  • Zeitschriftenartikel
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013)
  • Zeitschriftenartikel
    Do You Recognize That Building’s Façade?
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013) Ludwig, Bernd; Bienk, Stefan; Kattenbeck, Markus; Müller, Manuel; Ohm, Christina; Einmal, Michael; Glaser, Thomas; Hackl, Markus; Oreskovich, Mark; Schubart, Lea
    With the computational power of modern smartphones constantly increasing, resource intensive applications are becoming feasible to an ever growing extent. In this paper, we report on a research project recently started. Its aim is to develop an application for smartphones that combines pedestrian and public transport navigation including the computation of routes consisting of pedestrian routes and public transport trips and intuitive user guidance at any time of the trip. In particular, we focus on intuitive user guidance based on (LMs) in the surroundings of the user. For this reason, we use collaborative approaches to collect LMs and data about them.
  • Zeitschriftenartikel
    High Value Media Monitoring With Machine Learning
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013) Lyra, Matti; Clarke, Daoud; Morgan, Hamish; Reffin, Jeremy; Weir, David
    The Gorkana Group provides high quality media monitoring services to its clients. This paper describes an ongoing project aimed at increasing the amount of automation in Gorkana Group’s workflow through the application of machine learning and language processing technologies. It is important that Gorkana Group’s clients should have a very high level of confidence, that, if an article is relevant to one of their briefs, then they will be shown the article. However, delivering this high-quality media monitoring service means that humans are required to read through very large quantities of data, only a small portion of which is typically deemed relevant. The challenge being addressed by the work reported in this paper is how to efficiently achieve such high-quality media monitoring in the face of huge increases in the amount of the data that needs to be monitored. We show that, while machine learning can be applied successfully to this real world business problem, the constraints of the task give rise to a number of interesting challenges.
  • Zeitschriftenartikel
    Learning Tools for Agent-Based Modeling and Simulation
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013) Junges, Robert; Klügl, Franziska
    In this project report, we describe ongoing research on supporting the development of agent-based simulation models. The vision is that the agents themselves should learn their (individual) behavior model, instead of letting a human modeler test which of the many possible agent-level behaviors leads to the correct macro-level observations. To that aim, we integrate a suite of agent learning tools into SeSAm, a fully visual platform for agent-based simulation models. This integration is the focus of this contribution.
  • Zeitschriftenartikel
    From Supervised to Unsupervised Support Vector Machines and Applications in Astronomy
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013) Gieseke, Fabian
    Support vector machines are among the most popular techniques in machine learning. Given sufficient labeled data, they often yield excellent results. However, for a variety of real-world tasks, the acquisition of sufficient labeled data can be very time-consuming; unlabeled data, on the other hand, can often be obtained easily in huge quantities. Semi-supervised support vector machines try to take advantage of these additional unlabeled patterns and have been successfully applied in this context. However, they induce a hard combinatorial optimization problem. In this work, we present two optimization strategies that address this task and evaluate the potential of the resulting implementations on real-world data sets, including an example from the field of astronomy.
  • Zeitschriftenartikel
    Reinforcement Learning: Psychologische und neurobiologische Aspekte
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013) Tokic, Michel
    Mathematische Modelle von neurobiologisch und psychologisch inspirierten Lernparadigmen gelten als Schlüsseltechnologie für Problemstellungen, die anhand klassischer Programmierung schwer zu lösen sind. Reinforcement Learning ist in diesem Zusammenhang eines dieser Paradigmen, welches mittlerweile recht erfolgreich in der Praxis eingesetzt wird (u. a. in der Robotik), um Verhalten durch Versuch und Irrtum zu erlernen. In diesem Artikel möchte ich etwas näher auf die in Zusammenhang stehenden neurobiologischen und psychologischen Aspekte eingehen, welche das Vorbild einer Vielzahl mathematischer Modelle sind. Gesamtheitlich betrachtet ist Reinforcement Learning nicht ausschließlich für Lernen im Gehirn von Menschen und Tieren verantwortlich. Stattdessen findet ein großartiges Zusammenspiel mehrerer Paradigmen aus unterschiedlichen Hirnarealen statt, bei welchem auch Supervised- und Unsupervised Learning beteiligt sind.
  • Zeitschriftenartikel
    A Multi-objective Genetic Algorithm for Build Order Optimization in StarCraft II
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013) Köstler, Harald; Gmeiner, Björn
    This article presents a modified version of the multi-objective genetic algorithm NSGA II in order to find optimal opening strategies in the real-time strategy game StarCraft II. Based on an event-driven simulator capable of performing an accurate estimate of in-game build-times the quality of different build lists can be judged. These build lists are used as chromosomes within the genetic algorithm. Procedural constraints e.g. given by the Tech-Tree or other game mechanisms, are implicitly encoded into them. Typical goals are to find the build list producing most units of one or more certain types up to a certain time (Rush) or to produce one unit as early as possible (Tech-Push). Here, the number of entries in a build list varies and the objective values have in contrast to the search space a very small diversity. We introduce our game simulator including its graphical user interface, the modifications necessary to fit the genetic algorithm to our problem, test our algorithm on different Tech-Pushes and Rushes for all three races, and validate it with empirical data of expert StarCraft II players.
  • Zeitschriftenartikel
    Echtzeit-Videoanalyse im Fußball
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013) Schlipsing, Marc; Salmen, Jan; Igel, Christian
    Die Automatisierung der Videoanalyse nimmt im Profisport eine immer wichtigere Rolle ein. Im Fußball kommt dabei der Auswertung der Laufwege der Spieler eine besondere Bedeutung zu. Der vorliegende Bericht dokumentiert unser Kooperationsprojekt zum computergestützten Spieler-Tracking auf Basis von Videobildern in Echtzeit. Wir beschreiben den Aufbau und diskutieren die Praxistauglichkeit des entwickelten Systems, das sich durch hohe Genauigkeit, Mobilität und Kostengünstigkeit auszeichnet.
  • Zeitschriftenartikel
    Towards Automation of Simulation Studies
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013) Lattner, Andreas D.
    Simulation is applied in various domains to investigate different variants, to study effects, or to optimize models with respect to some performance measurement. Simulation models can exhibit a high level of complexity and thus, consist of many components and potentially many adjustable input parameters as well as a large number of output measurements. In this habilitation thesis, different methods in the fields of automation, data mining, and optimization in the context of simulation are developed. The underlying motivation is to increase the degree of automation and to increase the efficiency when performing simulation studies. The proposed methods are evaluated using three different simulation systems: Manufacturing simulation, traffic simulation, and gas dispersion simulation.
  • Zeitschriftenartikel
    Assistive Technology to Support the Mobility of Senior Citizens
    (KI - Künstliche Intelligenz: Vol. 27, No. 3, 2013) Schlieder, Christoph; Schmid, Ute; Munz, Michael; Stein, Klaus
    Maintaining mobility despite the bodily, mental, or monetary challenges which often come along with advanced age is a relevant aspect of the quality of live. The collaborative research project EMN-Moves provides assistive technology for initiating and coordinating mobility support in residential districts. Mobility support is seen as a social task involving the interplay of housing societies, social organisations and residents of different age groups—with and without special needs. The project focuses on two aspects: (1) a Geo-Wiki for documenting temporary mobility barriers and for generating proposals for alternative routes, (2) a matchmaking service for bringing together (elderly) people who need support with volunteers.