الگوریتم تصمیم‌گیری سطح بالا با تحلیل سیگنال‌های قطر مردمک

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی کامپیوتر، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران

2 دانشکده مهندسی کامپیوتر، دانشگاه تربیت دبیر شهید رجایی، تهران، ایران

چکیده

محققین سعی دارند با پیاده‌سازی الگوریتم‌های تصمیم‌گیری مشابه عملکرد مغز، به قدرت قابل‌توجه ذهن انسان دست یابند. تصمیم‌های سلسله مراتبی، تصمیمات پیچیده‌ای هستند که نیاز به مکانیزم‌های استدلال فراشناختی در مغز دارند. بازخورد منفی، قطعیت و قدرت محرک، پارامتر‌هایی هستند که در شکل‌گیری این نوع تصمیمات نقش دارند. در این پژوهش به‌ منظور ساخت یک چارچوب محاسباتی مشابه عملکرد مغز برای سیستم‌های هوشمند، درک ماهیت بیولوژی شکل‌گیری تصمیمات سطح بالا، استفاده از انواع دیگر داده‌ها علاوه بر داده‌های رفتاری نیز مهم خواهد بود. از آنجایی که پاسخ‌های غیرارادی چشمی حاصل از خروجی آزمایش روان-فیزیک، نماینده معتبری از عملکرد ساز و کار نورونی مغز می‌باشند، در این پژوهش علاوه بر تحلیل داده‌های رفتاری به این مسئله پرداخته شده است که آیا با تحلیل داده‌های غیرارادی انسان (سیگنال‌های چشمی) می‌توان به دینامیک حاکم بر تغییرات تصمیمات سطح بالا پی برد. دیده شد که اندازه قطر مردمک، احتمال تغییر در پارامترهای تصمیم‌های سطح بالا را پیش‌بینی می‌کند و بازتاب استراتژی تصمیم سطح بالای فرد تحت شرایط پیچیده است. سپس در راستای توسعه ابزار‌های مشابه عملکرد مغز در محیط‌های پیچیده، چارچوبی برای تصمیمات سلسله مراتبی ارائه شده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

High-level decision algorithm with analysis of pupil diameter signals

نویسندگان [English]

  • Leyla Yahyaie 1
  • Reza Ebrahimpour 2
  • Abass Koochari 1
1 Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
چکیده [English]

Researchers are trying to achieve the power of the human mind by implementing decision-making algorithms similar to brain function. Hierarchical decisions are complex decisions that require metacognitive reasoning mechanisms in the brain. Negative feedback, certainty, and motion strength are the parameters that play a role in shaping such decisions. In this study, in order to design a computational framework similar to brain function for intelligent systems, it will be important to understand the biology nature of high-level decision-making, using other types of data in addition to behavioral data. Since involuntary eye responses resulting from the output of psychophysical experiments are a reliable representative of the function of the neuronal mechanism in the brain, in this study addition to the analysis of behavioral data, this issue has been addressed whether it is possible to understand the dynamics of changes in high-level decisions by analyzing involuntary human data (eye signals). We found that pupil diameter size predicts the likelihood of changes in the parameters of high-level decisions, and reflects the individual's high-level decision strategy under complex conditions. Then, in order to design systems similar to brain function in complex environments, we provide a framework for hierarchical decisions.

کلیدواژه‌ها [English]

  • Intelligent systems
  • Hierarchical decision making
  • Pupil
  • Human

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