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Auflistung Künstliche Intelligenz 27(2) - Mai 2013 nach Titel
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- 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.
- 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.
- ZeitschriftenartikelCo-constructing Grounded Symbols—Feedback and Incremental Adaptation in Human–Agent Dialogue(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Buschmeier, Hendrik; Kopp, StefanGrounding 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.
- ZeitschriftenartikelEvolving Grounded Spatial Language Strategies(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Spranger, MichaelEach 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.
- 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.
- ZeitschriftenartikelGerman Journal on Artificial Intelligence(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Althoff, Klaus-Dieter
- 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.
- ZeitschriftenartikelHuman-Centered Robotics(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Visser, Ubbo
- ZeitschriftenartikelInterview with Prof. Stevan Harnad(KI - Künstliche Intelligenz: Vol. 27, No. 2, 2013) Coradeschi, Silvia
- 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.