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Künstliche Intelligenz 27(2) - Mai 2013

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  • Zeitschriftenartikel
    Stream-Based Hierarchical Anchoring
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Heintz, Fredrik; Kvarnström, Jonas; Doherty, Patrick
    Autonomous systems situated in the real world often need to recognize, track, and reason about various types of physical objects. In order to allow reasoning at a symbolic level, one must create and continuously maintain a correlation between symbols denoting physical objects and sensor data being collected about them, a process called anchoring.In this paper we present a stream-based hierarchical anchoring framework. A classification hierarchy is associated with expressive conditions for hypothesizing the type and identity of an object given streams of temporally tagged sensor data. The anchoring process constructs and maintains a set of object linkage structures representing the best possible hypotheses at any time. Each hypothesis can be incrementally generalized or narrowed down as new sensor data arrives. Symbols can be associated with an object at any level of classification, permitting symbolic reasoning on different levels of abstraction. The approach is integrated in the DyKnow knowledge processing middleware and has been applied to an unmanned aerial vehicle traffic monitoring application.
  • Zeitschriftenartikel
    Evolving Grounded Spatial Language Strategies
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Spranger, Michael
    Each natural language phrase is evidence for a particular strategy of construing reality. One domain where this has been extensively studied is spatial language, which reveals an enormous amount of variation of conceptualization strategies both within a particular language and cross-culturally. This paper proposes a computational formalism for representing conceptualization strategies and shows how the formalism can be used to study and explain the evolution and emergence of spatial conceptualization strategies and their impact on shared grounded communication systems.
  • Zeitschriftenartikel
    Anchoring Social Symbol Grounding in Children’s Interactions
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Vogt, Paul; Mastin, J. Douglas
    In this article, we will discuss how computational social symbol grounding (i.e. how shared sets of symbols are grounded in multi-agent models) can be used to study children’s acquisition of word-meaning mappings. In order to use multi-agent modelling as a reliable tool to study human language acquisition, we argue that the simulations need to be anchored in observations of social interactions that children encounter “in the wild” and in different cultures. We discuss what aspects of such social interactions and cognitive mechanisms can and should be modelled, as well as how we intend to anchor this model to corpora containing features of children’s social behaviour as observed “in the wild” to mimic children’s (social) environment as reliably as possible. In addition, we discuss some challenges that need to be solved in order to construct the computational model. The resulting SCAFFOLD model will provide a benchmark for investigating socio-cognitive mechanisms of human social symbol grounding using computer simulations.
  • Zeitschriftenartikel
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013)
  • Zeitschriftenartikel
    Co-constructing Grounded Symbols—Feedback and Incremental Adaptation in Human–Agent Dialogue
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Buschmeier, Hendrik; Kopp, Stefan
    Grounding in dialogue concerns the question of how the gap between the individual symbol systems of interlocutors can be bridged so that mutual understanding is possible. This problem is highly relevant to human–agent interaction where mis- or non-understanding is common. We argue that humans minimise this gap by collaboratively and iteratively creating a shared conceptualisation that serves as a basis for negotiating symbol meaning. We then present a computational model that enables an artificial conversational agent to estimate the user’s mental state (in terms of contact, perception, understanding, acceptance, agreement and based upon his or her feedback signals) and use this information to incrementally adapt its ongoing communicative actions to the user’s needs. These basic abilities are important to reduce friction in the iterative coordination process of co-constructing grounded symbols in dialogue.
  • Zeitschriftenartikel
    From Object Recognition to Activity Interpretation and Back, Based on Point Cloud Data
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Albrecht, Sven; Wiemann, Thomas; Hertzberg, Joachim; Guesgen, Hans W.; Marsland, Stephen
    Semantic mapping of static environments has become a hot topic in robotics. The aim of the Mermaid project was to investigate the transfer of a sensor data interpretation approach for mapping to the problem of activity recognition in smart home applications such as elderly care. The basic structure of the semantic mapping approach, i.e., to assemble hypotheses of object aggregates in a closed-loop process of bottom-up raw data interpretation and top-down expectation generation from a domain ontology, can be extended to the temporal domain to include activity interpretation. This paper reports initial results, based on a study using point clouds from depth (RGB-D) sensor data.
  • Zeitschriftenartikel
    On Grounding Natural Kind Terms in Human-Robot Communication
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Peltason, Julia; Rieser, Hannes; Wachsmuth, Sven; Wrede, Britta
    Our contribution situates Human-Robot Communication, especially the grounding of Natural Kind Terms, in the interface of Artificial Intelligence, Cognitive Psychology, Philosophy, Robotics and Semantics. We investigate whether a robot can be grounded in the sense favoured in Artificial Intelligence and Philosophy.We thus extend the notion of grounding to social symbol grounding using an interactive perspective addressing the question how grounding can be achieved in detail in interaction. For the acquisition of Natural Kind Terms we establish the notions of foundational common ground and foundational grounding in contrast to the established common ground and grounding. We introduce the robot setting used and provide a deep evaluation of a tutorial dialogue between a user and the robot. We investigate these Human-Robot Communication data from an ethno-methodological and an “omniscient” perspective (the latter amounting to consideration of automatic speech recognition results) and test whether these perspectives matter for analysing grounding. We show that the robot has acquired a partial concept of a Natural Kind Term—represented by statistics over visual object features—and that this is shared knowledge, hence the first step of a grounding sequence. Finally, we argue that grounding of robots can be achieved and extended to situated structures of considerable complexity.
  • Zeitschriftenartikel
    A Short Review of Symbol Grounding in Robotic and Intelligent Systems
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Coradeschi, Silvia; Loutfi, Amy; Wrede, Britta
    This paper gives an overview of the research papers published in Symbol Grounding in the period from the beginning of the 21st century up 2012. The focus is in the use of symbol grounding for robotics and intelligent system. The review covers a number of subtopics, that include, physical symbol grounding, social symbol grounding, symbol grounding for vision systems, anchoring in robotic systems, and learning symbol grounding in software systems and robotics. This review is published in conjunction with a special issue on Symbol Grounding in the Künstliche Intelligenz Journal.
  • Zeitschriftenartikel
    Grounding the Interaction: Knowledge Management for Interactive Robots
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Lemaignan, Séverin
    The dissertation tackles the broad question of knowledge representation and manipulation for companion robots. It first builds a taxonomy of the knowledge manipulation skills required by service robots, then proposes a novel active knowledge base that integrates into large cognitive architectures, and finally explores several applications, including natural language grounding.
  • Zeitschriftenartikel
    Symbol Grounding as Social, Situated Construction of Meaning in Human-Robot Interaction
    (KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Kruijff, Geert-Jan M.
    The paper views the issue of “symbol grounding” from the viewpoint of the construction of meaning between humans and robots, in the context of a collaborative activity. This concerns a core aspect of the formation of common ground: The construction of meaning between actors as a conceptual representation which is believed to be mutually understood as referring to a particular aspect of reality. The problem in this construction is that experience is inherently subjective—and more specifically, humans and robots experience and understand reality fundamentally differently. There is an inherent asymmetry between the actors involved. The paper focuses on how this asymmetry can be reflected logically, and particularly in the underlying model theory. The point is to make it possible for a robot to reason explicitly both about such asymmetry in understanding, consider possibilities for alignment to deal with it, and establish (from its viewpoint) a level of intersubjective or mutual understanding. Key to the approach taken in the paper is to consider conceptual representations to be formulas over propositions which are based in proofs, as reasoned explanations of experience. This shifts the focus from a notion of “truth” to a notion of judgment—judgments which can be subjectively right and still intersubjectively wrong (faultless disagreement), and which can evolve over time (updates, revision). The result is an approach which accommodates both asymmetric agency and social sentience, modelling symbol grounding in human-robot interaction as social, situated construction over time.