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Decisions and Performance Under Bounded Rationality: A Computational Benchmarking Approach

Author

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  • Dainis Zegners
  • Uwe Sunde
  • Anthony Strittmatter

Abstract

This paper presents a novel approach to analyze human decision-making that involves comparing the behavior of professional chess players relative to a computational benchmark of cognitively bounded rationality. This benchmark is constructed using algorithms of modern chess engines and allows investigating behavior at the level of individual move-by-move observations, thus representing a natural benchmark for computationally bounded optimization. The analysis delivers novel insights by isolating deviations from this benchmark of bounded rationality as well as their causes and consequences for performance. The findings document the existence of several distinct dimensions of behavioral deviations, which are related to asymmetric positional evaluation in terms of losses and gains, time pressure, fatigue, and complexity. The results also document that deviations from the benchmark do not necessarily entail worse performance. Faster decisions are associated with more frequent deviations from the benchmark, yet they are also associated with better performance. The findings are consistent with an important influence of intuition and experience, thereby shedding new light on the recent debate about computational rationality in cognitive processes.

Suggested Citation

  • Dainis Zegners & Uwe Sunde & Anthony Strittmatter, 2020. "Decisions and Performance Under Bounded Rationality: A Computational Benchmarking Approach," CESifo Working Paper Series 8341, CESifo.
  • Handle: RePEc:ces:ceswps:_8341
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    References listed on IDEAS

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    Cited by:

    1. Mehmet S. Ismail, 2023. "Human and Machine Intelligence in n-Person Games with Partial Knowledge," Papers 2302.13937, arXiv.org, revised Mar 2023.

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    More about this item

    Keywords

    cognitively bounded rationality; benchmark computing; artificial intelligence; decision quality; decision time;
    All these keywords.

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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