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oapen-20.500.12657-598372022-12-06T03:08:13Z Adaptive Umweltmodellierung für kognitive Systeme in offener Welt durch dynamische Konzepte und quantitative Modellbewertung Kuwertz, Achim Christian Umweltmodellierung quantitative Modellbewertung probabilistische Informationsverarbeitung Konzeptlernen kognitive Systeme world modeling quantitative model evaluation concept learning probabilistic information processing cognitive systems bic Book Industry Communication::U Computing & information technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists In this work, an approach for adaptive world modeling is proposed. World models for cognitive systems often employ predefined domain models, which may become insufficient when encountering unforeseen entities. The presented approach addresses an adaptive extension of such domain models, considering the relevance of proposed model adaptations. As a basis, a quantitative model evaluation is devised, rating the ability of a domain model to represent the currently observed environment state. 2022-12-05T15:40:40Z 2022-12-05T15:40:40Z 2022 book ONIX_20221205_9783731512196_10 1863-6489 9783731512196 https://library.oapen.org/handle/20.500.12657/59837 ger Karlsruher Schriften zur Anthropomatik application/pdf n/a 9783731512196.pdf https://doi.org/10.5445/KSP/1000150865 KIT Scientific Publishing KIT Scientific Publishing 10.5445/KSP/1000148667 In this work, an approach for adaptive world modeling is proposed. World models for cognitive systems often employ predefined domain models, which may become insufficient when encountering unforeseen entities. The presented approach addresses an adaptive extension of such domain models, considering the relevance of proposed model adaptations. As a basis, a quantitative model evaluation is devised, rating the ability of a domain model to represent the currently observed environment state. 10.5445/KSP/1000148667 44e29711-8d53-496b-85cc-3d10c9469be9 9783731512196 KIT Scientific Publishing 57 440 Karlsruhe open access
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In this work, an approach for adaptive world modeling is proposed. World models for cognitive systems often employ predefined domain models, which may become insufficient when encountering unforeseen entities. The presented approach addresses an adaptive extension of such domain models, considering the relevance of proposed model adaptations. As a basis, a quantitative model evaluation is devised, rating the ability of a domain model to represent the currently observed environment state.
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