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02479nma a2200469 u 4500 |
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EBX01000000000000001194579 |
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220822 ||| eng |
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|a 978-3-030-69823-2
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| 020 |
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|a 9783030698232
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| 100 |
1 |
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|a Bechberger, Lucas
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| 245 |
0 |
0 |
|a Concepts in Action
|h Elektronische Ressource
|b Representation, Learning, and Application
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| 260 |
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|b Springer Nature
|c 2021
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| 300 |
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|a 1 electronic resource (194 p.)
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| 653 |
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|a Robotics and Typicality
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| 653 |
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|a Artificial intelligence / bicssc
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| 653 |
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|a Conceptual Spaces
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| 653 |
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|a Learning, Language and Application
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| 653 |
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|a Philosophy: logic / bicssc
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| 653 |
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|a Concept Research and Machine Learning
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| 653 |
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|a Concept Research
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| 653 |
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|a Philosophy of mind / bicssc
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| 653 |
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|a Language: history and general works / bicssc
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| 653 |
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|a Compositionality and Concepts
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| 653 |
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|a Concept and Representation
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| 700 |
1 |
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|a Kühnberger, Kai-Uwe
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| 700 |
1 |
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|a Liu, Mingya
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| 700 |
1 |
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|a Bechberger, Lucas
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 490 |
0 |
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|a Language, Cognition, and Mind
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| 500 |
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|a Creative Commons (cc), by/4.0/, http://creativecommons.org/licenses/by/4.0/
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| 028 |
5 |
0 |
|a 10.1007/978-3-030-69823-2
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/71654
|z DOAB: description of the publication
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| 856 |
4 |
0 |
|u https://library.oapen.org/bitstream/20.500.12657/50408/1/978-3-030-69823-2.pdf
|7 0
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 400
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| 082 |
0 |
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|a 900
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| 082 |
0 |
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|a 700
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| 082 |
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|a 100
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| 520 |
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|a This open access book is a timely contribution in presenting recent issues, approaches, and results that are not only central to the highly interdisciplinary field of concept research but also particularly important to newly emergent paradigms and challenges. The contributors present a unique, holistic picture for the understanding and use of concepts from a wide range of fields including cognitive science, linguistics, philosophy, psychology, artificial intelligence, and computer science. The chapters focus on three distinct points of view that lie at the core of concept research: representation, learning, and application. The contributions present a combination of theoretical, experimental, computational, and applied methods that appeal to students and researchers working in these fields.
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