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- ZeitschriftenartikelGerman Journal on Artificial Intelligence(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Althoff, Klaus-Dieter
- ZeitschriftenartikelFrom 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, StephenSemantic 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.
- ZeitschriftenartikelOn Grounding Natural Kind Terms in Human-Robot Communication(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Peltason, Julia; Rieser, Hannes; Wachsmuth, Sven; Wrede, BrittaOur 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.
- ZeitschriftenartikelA Short Review of Symbol Grounding in Robotic and Intelligent Systems(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Coradeschi, Silvia; Loutfi, Amy; Wrede, BrittaThis 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.
- ZeitschriftenartikelGrounding the Interaction: Knowledge Management for Interactive Robots(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Lemaignan, SéverinThe 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.
- ZeitschriftenartikelSymbol 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.
- ZeitschriftenartikelHuman-Centered Robotics(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Visser, Ubbo
- ZeitschriftenartikelKnowledge Based Perceptual Anchoring(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Daoutis, MariosPerceptual anchoring is the process of creating and maintaining a connection between the sensor data corresponding to a physical object and its symbolic description. It is a subset of the symbol grounding problem, introduced by Harnad (Phys. D, Nonlinear Phenom. 42(1–3):335–346, 1990) and investigated over the past years in several disciplines including robotics. This PhD dissertation focuses on a method for grounding sensor data of physical objects to the corresponding semantic descriptions, in the context of cognitive robots where the challenge is to establish the connection between percepts and concepts referring to objects, their relations and properties. We examine how knowledge representation can be used together with an anchoring framework, so as to complement the meaning of percepts while supporting better linguistic interaction with the use of the corresponding concepts. The proposed method addresses the need to represent and process both perceptual and semantic knowledge, often expressed in different abstraction levels, while originating from different modalities. We then focus on the integration of anchoring with a large scale knowledge base system and with perceptual routines. This integration is applied in a number of studies, where in the context of a smart home, several evaluations spanning from spatial and commonsense reasoning to linguistic interaction and concept acquisition.
- ZeitschriftenartikelAnchoring Social Symbol Grounding in Children’s Interactions(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Vogt, Paul; Mastin, J. DouglasIn 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.
- ZeitschriftenartikelNews(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013)