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Determining an individual’s strategic reasoning capability based solely on choice data is a complex task. This complexity arises because sophisticated players might have non-equilibrium beliefs about others, leading to non-equilibrium actions. In our study, we pair human participants with computer players known to be fully rational. This use of robot players allows us to disentangle limited reasoning capacity from belief formation and social biases. Our results show that, when paired with robots, subjects consistently demonstrate higher levels of rationality, compared to when paired with human players. Furthermore, players’ rationality levels are relatively stable across games when paired with robot players, even though those with intermediate rationality levels exhibit inconsistency across games. Leveraging our experimental design, we identify and document potential causes of this inconsistency.
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This content will become publicly available on August 1, 2026
A Quantitative Analysis of Rational Decisions Under Uncertainty in Engineering Systems Design
Rational decision-making is crucial in the later stages of engineering system design to allocate resources efficiently and minimize costs. However, human rationality is bounded by cognitive biases and limitations. Understanding how humans deviate from rationality is critical for guiding designers toward better design outcomes. In this paper, we quantify designer rationality in competitive scenarios based on utility theory. Using an experiment inspired by crowd-sourced contests, we show that designers employ varied search strategies. Some participants approximate a Bayesian agent that aimed to maximize its expected utility. Those with higher rationality reduce uncertainty more effectively. Furthermore, rationality correlates with both the proximity to optimal design and design iteration costs, with winning participants exhibiting greater rationality than losing participants.
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- Award ID(s):
- 2419423
- PAR ID:
- 10636310
- Publisher / Repository:
- Cambridge University Press
- Date Published:
- Journal Name:
- Proceedings of the Design Society
- Volume:
- 5
- Issue:
- ICED2025
- ISSN:
- 2732-527X
- Page Range / eLocation ID:
- 249 to 258
- Subject(s) / Keyword(s):
- bounded rationality utility theory decision under uncertainty Bayesian optimization
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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