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Gaming the System: An Agent-Based Model of Estimation Strategies and Their Effects on System Performance

[+] Author Affiliations
John Meluso, Jesse Austin-Breneman

University of Michigan, Ann Arbor, MI

Paper No. DETC2017-68202, pp. V02AT03A050; 10 pages
doi:10.1115/DETC2017-68202
From:
  • ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2A: 43rd Design Automation Conference
  • Cleveland, Ohio, USA, August 6–9, 2017
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5812-7
  • Copyright © 2017 by ASME

abstract

Parameter estimates in large-scale complex engineered systems affect system evolution yet can be difficult and expensive to test. Systems engineering uses analytical methods to reduce uncertainty, but a growing body of work from other disciplines indicates that cognitive heuristics also affect decision-making. Interviews with several expert aerospace practitioners suggest that engineers bias estimation strategies. Practitioners reaffirmed known system features and posited that engineers may bias estimation methods as a negotiation and resource conservation strategy. Specifically, participants reported that some systems engineers “game the system” by biasing requirements to counteract subsystem estimation biases. An agent-based model simulation which recreates these characteristics is presented. Model results suggest that the systems engineers’ “gaming” strategy of counteracting subsystem bias may decrease system-level estimate accuracy and increase uncertainty.

Copyright © 2017 by ASME

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