Imitation of Life: A Search Engine for Biologically Inspired Design

Hen Emuna, Nadav Borenstein, Xin Qian, Hyeonsu Kang, Joel Chan, Aniket Kittur, Dafna Shahaf

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Biologically Inspired Design (BID), or Biomimicry, is a problem-solving methodology that applies analogies from nature to solve engineering challenges. For example, Speedo engineers designed swimsuits based on shark skin. Finding relevant biological solutions for real-world problems poses significant challenges, both due to the limited biological knowledge engineers and designers typically possess and to the limited BID resources. Existing BID datasets are hand-curated and small, and scaling them up requires costly human annotations. In this paper, we introduce BARCODE (Biological Analogy Retriever), a search engine for automatically mining bio-inspirations from the web at scale. Using advances in natural language understanding and data programming, BARCODE identifies potential inspirations for engineering challenges. Our experiments demonstrate that BARCODE can retrieve inspirations that are valuable to engineers and designers tackling real-world problems, as well as recover famous historical BID examples. We release data and code; we view BARCODE as a step towards addressing the challenges that have historically hindered the practical application of BID to engineering innovation.

Original languageAmerican English
Title of host publicationTechnical Tracks 14
EditorsMichael Wooldridge, Jennifer Dy, Sriraam Natarajan
PublisherAssociation for the Advancement of Artificial Intelligence
Pages503-511
Number of pages9
Edition1
ISBN (Electronic)1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 1577358872, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879, 9781577358879
DOIs
StatePublished - 25 Mar 2024
Event38th AAAI Conference on Artificial Intelligence, AAAI 2024 - Vancouver, Canada
Duration: 20 Feb 202427 Feb 2024

Publication series

NameProceedings of the AAAI Conference on Artificial Intelligence
Number1
Volume38
ISSN (Print)2159-5399
ISSN (Electronic)2374-3468

Conference

Conference38th AAAI Conference on Artificial Intelligence, AAAI 2024
Country/TerritoryCanada
CityVancouver
Period20/02/2427/02/24

Bibliographical note

Publisher Copyright:
Copyright © 2024, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

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