Collaborative Research: Design Decisions under Competition at the Edge of Bounded Rationality: Quantification, Models, and Experiments

协作研究：有限理性边缘竞争下的设计决策：量化、模型和实验

• 批准号: 2321463
• 负责人: Zhenghui Sha
• 金额: $ 28.27万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321463&HistoricalAwards=false
• 关键词: Collaborative; Research; Design; Decisions; under

The objective of this project is to investigate the impact of information uncertainty on design rationality under competition among teams and to develop a competition-aware artificial intelligence (AI) assistant for design space exploration and exploitation. Communication issues have been broadly recognized as a critical factor that impacts design outcomes in team decisions, because the information shared during communication can be incomplete and imperfect. Therefore, addressing such issues by understanding the role of information uncertainty on human design decisions in teams could lead to better coordination of team decisions, advancement in human-AI collaborations, and significant cost savings in large-scale engineering design projects. However, despite the significant progress in modeling design decision-making in teams, current literature neglects two fundamental aspects of the design process: human designers have bounded rationality, and most design activities happen under competition, whether consciously or unconsciously. This project is motivated to fill this gap by developing theoretical and experimental constructs to computationally model human designers’ sequential decisions in a competitive environment and to experimentally measure their bounded rationality. The expected outcome is a suite of new knowledge, including metrics, models, algorithms, and testbeds, on human behavior in design teams under competition in the presence of uncertainties. Broader impacts will be generated by directly engaging diverse undergraduate students in research activities through the Freshman Introduction to Research in Engineering (FIRE) program at the University of Texas at Austin and the Pinnacle and Clark Scholars programs at Stevens Institute of Technology.This project is driven by answering two research questions: 1) what are the effects of information uncertainty (e.g., when design information shared between team members is incomplete) on design rationality under competition among teams? 2) How would such effects differ across a wider range of team sizes? To answer the two questions, an interdisciplinary research approach is planned that combines descriptive, prescriptive, and predictive analytics. In particular, we will develop game theoretic models to model sequential design decisions under competition, synergistically integrating two types of sequential learning models, i.e., theory-driven prescriptive models (e.g., Bayesian optimization) and data-driven predictive models (e.g., long-short term memory units). The new approach explicitly models designers’ perceptions of their opponents’ past performance and predicts the opponent’s future decisions, thereby providing a quantitative way to study the influence of uncertain information shared among designers in a team on their decisions in competition against other teams. Experiments will be conducted to collect behavioral data to study how human irrationality, benchmarking on rational behaviors predicted by the theoretical models, would change over time during the course of the design competition. The research findings will be validated in a real-world design challenge on solar system design, where multiple teams compete for awards. To benefit a broader research community, this project will build an open design infrastructure to share the project data and findings.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的目的是调查信息不确定性对团队之间竞争中设计合理性的影响，并为设计空间探索和开发的竞争感知人工智能（AI）助理。沟通问题已被广泛认为是影响团队决策中设计成果的关键因素，因为在交流过程中共享的信息可能是不完整和不完美的。因此，通过了解信息不确定性在团队中的人力设计决策中的作用来解决此类问题，可以更好地协调团队决策，人类合作的进步以及大规模工程设计项目中的大量成本节省。但是，尽管在团队中建模设计决策方面取得了重大进展，但当前的文献却忽略了设计过程的两个基本方面：人类设计师的合理性有限，大多数设计活动都在竞争中发生，无论是有意识或无意识的。该项目是通过在竞争环境中开发理论和实验性结构来建模人类设计师的顺序决策并在实验中衡量其有限的理性的，以填补这一空白。预期的结果是一系列新知识，包括指标，模型，算法和测试床，这些在不确定性存在下竞争的设计团队中的人类行为。通过直接吸引潜水员的本科生通过新生在奥斯汀大学的工程研究（FIRE）计划（FIRE）计划以及史蒂文斯技术研究所的Pinnacle和Clark Scholars计划中，将产生更大的影响。 2）在各种团队规模的范围内，这种效果会有何不同？为了回答这两个问题，计划了一种跨学科研究方法，该方法结合了描述性，规范性和预测性分析。特别是，我们将开发游戏理论模型，以建模竞争下的顺序设计决策，协同整合两种类型的顺序学习模型，即理论驱动的规范模型（例如，贝叶斯优化）和数据驱动的预测模型（例如，长期任期内存单位）。这种新方法明确地模拟了设计师对选项的过去绩效的看法，并预测了选项的未来决策，从而提供了一种定量方法来研究团队中设计师之间不确定信息在与其他团队竞争中的决策中共享的不确定信息的影响。将进行实验以收集行为数据，以研究人类的非理性性，基于理论模型预测的理性行为的基准如何随着时间的推移而在设计竞争过程中随着时间而变化。研究结果将在太阳系设计的现实设计挑战中得到验证，该设计挑战多个团队竞争奖项。为了使更广泛的研究社区受益，该项目将建立一个开放的设计基础架构来共享项目数据和发现。该奖项反映了NSF的法定任务，并且我们使用基金会的知识分子优点和更广泛的影响审查标准，通过评估诚实地表示支持。