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Cognitive and Agent-based Design Met...

Egan, Paul F.

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Cognitive and Agent-based Design Methodologies for Engineering Complex Biological Systems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Cognitive and Agent-based Design Methodologies for Engineering Complex Biological Systems./
作者:	Egan, Paul F.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2014,
面頁冊數:	248 p.
附註:	Source: Dissertation Abstracts International, Volume: 76-06(E), Section: B.
Contained By:	Dissertation Abstracts International76-06B(E).
標題:	Mechanical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3648735
ISBN:	9781321477634

Cognitive and Agent-based Design Methodologies for Engineering Complex Biological Systems.
Egan, Paul F.

Cognitive and Agent-based Design Methodologies for Engineering Complex Biological Systems. - Ann Arbor : ProQuest Dissertations & Theses, 2014 - 248 p.

Source: Dissertation Abstracts International, Volume: 76-06(E), Section: B.

Thesis (Ph.D.)--Carnegie Mellon University, 2014.

As engineered systems become increasingly more complex, the limitations of traditional engineering approaches for handling designs containing many parts and scales with counter-intuitive emergent behavior is becoming readily more apparent. Throughout this Dissertation, we develop integrative cognitive and agent-based design methodologies that improve upon the state of the art in complex systems design from multiple perspectives. Myosin biomolecular motor systems are utilized as a vessel for developing these design methods, and are particularly well-suited as a case study because myosin-based technologies embody many facets of complex systems, such as bridging nano- to macro- scales with many layers of emergent behavior.

ISBN: 9781321477634Subjects--Topical Terms:

649730
Mechanical engineering.

Cognitive and Agent-based Design Methodologies for Engineering Complex Biological Systems.
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500 $a Source: Dissertation Abstracts International, Volume: 76-06(E), Section: B.
500 $a Adviser: Jonathan Cagan.
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520 $a As engineered systems become increasingly more complex, the limitations of traditional engineering approaches for handling designs containing many parts and scales with counter-intuitive emergent behavior is becoming readily more apparent. Throughout this Dissertation, we develop integrative cognitive and agent-based design methodologies that improve upon the state of the art in complex systems design from multiple perspectives. Myosin biomolecular motor systems are utilized as a vessel for developing these design methods, and are particularly well-suited as a case study because myosin-based technologies embody many facets of complex systems, such as bridging nano- to macro- scales with many layers of emergent behavior.
520 $a The first developed method integrated a multi-agent molecular simulation that recreates emergent behavior with structure-behavior-function representations that could aid engineers' understanding and reasoning about myosin-based systems. The multi-agent simulation was demonstrated to provide insights relating individual molecular alterations to global system performance, resulting in the discovery of design principles that simplify analysis for human designers. Further synergistic methods were developed through cognitive studies that sought to improve user design proficiency with our myosin design graphical user interface, when users were populations of mechanical engineering students. User design searches were tracked and informed cognitive-based search strategies to implement and refine with software agents; when these strategies were returned to users, empirical studies demonstrated an improvement in user search proficiency. Further cognitive studies showed that users learning via interactions with agent-based simulation renderings had improved understanding and design proficiency, compared to when users designed with no prior support. A final integrative methodology informed by cognitive studies utilized distributed agent teams to embody and optimize many potential myosin technologies simultaneously (myosin meta-Systems), with an approach informed by wet-lab experiments and reverse engineered molecular models.
520 $a As a whole, these findings have led to significant improvements in design methods for complex systems, and are supported empirically. These methods led to novel discoveries in the domain of myosin-based design, and were developed in a manner to promote domain-independence. They therefore retain extensibility for aiding engineers in overcoming the challenges of complexity across many interesting and exciting and technological endeavors.
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