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International Conference on Case-Based Reasoning

ICCBR 2011: Case-Based Reasoning Research and Development pp 334–347Cite as

Representation, Indexing, and Retrieval of Biological Cases for Biologically Inspired Design

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6880))

Abstract

Biologically inspired design is an increasingly popular design paradigm. Biologically inspired design differs from many traditional case-based reasoning tasks because it employs cross-domain analogies. The wide differences in biological source cases and technological target problems present challenges for determining what would make good or useful schemes for case representation, indexing, and adaptation. In this paper, we provide an information-processing analysis of biologically inspired design, a scheme for representing knowledge of designs of biological systems, and a computational technique for automatic indexing and retrieval of biological analogues of engineering problems. Our results highlight some important issues that a case-based reasoning system must overcome to succeed in supporting biologically inspired design.

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Author information

Authors and Affiliations

  1. Design & Intelligence Laboratory, School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, USA

    Bryan Wiltgen, Ashok K. Goel & Swaroop Vattam

  2. Center for Biologically Inspired Design, Georgia Institute of Technology, Atlanta, GA, USA

    Ashok K. Goel

Authors
  1. Bryan Wiltgen
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  2. Ashok K. Goel
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  3. Swaroop Vattam
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Ashwin Ram Nirmalie Wiratunga

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Wiltgen, B., Goel, A.K., Vattam, S. (2011). Representation, Indexing, and Retrieval of Biological Cases for Biologically Inspired Design. In: Ram, A., Wiratunga, N. (eds) Case-Based Reasoning Research and Development. ICCBR 2011. Lecture Notes in Computer Science(), vol 6880. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23291-6_25

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  • DOI: https://doi.org/10.1007/978-3-642-23291-6_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23290-9

  • Online ISBN: 978-3-642-23291-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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