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Auflistung nach Autor:in "Eichhorn, Christian"

1 - 5 von 5
  • Zeitschriftenartikel
    A Practical Comparison of Qualitative Inferences with Preferred Ranking Models
    (KI - Künstliche Intelligenz: Vol. 31, No. 1, 2017) Beierle, Christoph; Eichhorn, Christian; Kutsch, Steven
    When reasoning qualitatively from a conditional knowledge base, two established approaches are system Z and p-entailment. The latter infers skeptically over all ranking models of the knowledge base, while system Z uses the unique pareto-minimal ranking model for the inference relations. Between these two extremes of using all or just one ranking model, the approach of c-representations generates a subset of all ranking models with certain constraints. Recent work shows that skeptical inference over all c-representations of a knowledge base includes and extends p-entailment. In this paper, we follow the idea of using preferred models of the knowledge base instead of the set of all models as a base for the inference relation. We employ different minimality constraints for c-representations and demonstrate inference relations from sets of preferred c-representations with respect to these constraints. We present a practical tool for automatic c-inference that is based on a high-level, declarative constraint-logic programming approach. Using our implementation, we illustrate that different minimality constraints lead to inference relations that differ mutually as well as from system Z and p-entailment.
  • Journal
    Dissertation Abstract: Qualitative Rational Reasoning with Finite Conditional Knowledge Bases
    (KI - Künstliche Intelligenz: Vol. 33, No. 1, 2019) Eichhorn, Christian
  • Konferenzbeitrag
    Generating an Environment for Socializing Between Older Adults in a VR Supermarket
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Walchshäusl, Sebastian; Eichhorn, Christian; Plecher, David A.; Simecek, Tim; Klinker, Gudrun; Hiyama, Atsushi; Inami, Matsuko
    Socialization is crucial for the well-being of individuals, but elderly people often face challenges due to physical and psychological issues, as well as the COVID-19 pandemic. To address this issue, a novel approach has been developed using a Japanese Virtual Reality (VR) supermarket, where older adults can purchase products that could be delivered to their homes while socializing with others in a familiar environment. The VR supermarket is based on Japanese supermarket shelf layouts, with hand-tracking and gestures used for interaction. Avatars, attached with images of the participants and their synchronized voice input are used to represent them. In a user study involving 14 older adults, the application was found to be effective for social communication, and potential negative effects such as cybersickness were successfully mitigated. The VR supermarket thus provides a valuable tool for older adults to socialize and meet their need to interact with people from the same age group, even in isolation (pandemic scenario).
  • long
    On the Trail of Jack the Ripper- A Serious AR Game about a Cold Case
    (GI VR / AR Workshop, 2021) Plecher, David; Müller, Andrea; Eichhorn, Christian; Klinker, Gudrun
  • Zeitschriftenartikel
    Qualitative and Semi-Quantitative Inductive Reasoning with Conditionals
    (KI - Künstliche Intelligenz: Vol. 29, No. 3, 2015) Eichhorn, Christian; Kern-Isberner, Gabriele
    Conditionals like “birds fly—if bird then fly” are crucial for commonsense reasoning. In this technical project report we show that conditional logics provide a powerful formal framework that helps understanding if-then sentences in a way that is much closer to human reasoning than classical logic and allows for high-quality reasoning methods. We describe methods that inductively generate models from conditional knowledge bases. For this, we use both qualitative (like preferential models) and semi-quantitative (like Spohn’s ranking functions) semantics. We show similarities and differences between the resulting inference relations with respect to formal properties. We further report on two graphical methods on top of the ranking approaches which allow to decompose the models into smaller, more feasible components and allow for local inferences.