مروری بر مدل¬های انگیزش درونی یادگیری ماشین
الموضوعات : Computer Engineering and IT
سعید جمالی
1
,
سعید ستایشی
2
,
محسن جهانشاهی
3
,
سجاد تقوایی
4
1 - دانشکده فنی مهندسی، دانشگاه آزاد اسلامی واحد تهران مرکزی، تهران، ایران
2 - دانشکده فیزیک و مهندسی انرژی، دانشگاه صنعتی امیرکبیر، تهران، ایران
3 - دانشکده فنی مهندسی، دانشگاه آزاد اسلامی واحد تهران مرکزی، تهران، ایران
4 - دانشکده مهندسی مکانیک، دانشگاه شیراز، شیراز، ایران
الکلمات المفتاحية: علوم‌شناختی, انگیزش درونی, یادگیری ماشین, یادگیری تقویتی, محیط‌های خلوت (اسپارس), جستجو,
ملخص المقالة :
امروزه انگیزش، توجه فزایندهای را به خود جلب کرده است؛ زیرا که به موجود زنده و ربات اجازه میدهد در فقدان راهنماییِ انگیزش بیرونی (پاداش از محیط)، دانش و مهارت را بهصورت تجمعی و کاملاً خودمختار اخذ نماید. علاوه بر روان‌شناسی و علوم اعصاب، این مدلها چشم‌انداز جدیدی را در هوش مصنوعی ایجاد کردهاند. معماریهای الگوریتمی انگیزش درونی در اکتشاف، امکان اخذ مهارتهای حرکتیِ مؤثری را در مسائل به وجود میآورند. از طرفی بسیاری از مسائل دنیای واقعی دارای چنین خصوصیتی هستند که در بخشهای زیادی از محیط، پاداشی از محیط وجود ندارد. در نتیجه، این موضوع نه‌تنها از لحاظ نظری اهمیت بسزایی در بهبود الگوریتمهای هوش مصنوعی مخصوصاً در بحث اکتشاف دارد، بلکه به لحاظ کاربردی و عملی نیز میتواند در کاربردهای واقعی و یا نزدیک به واقعیت مورداستفاده قرار گیرد. این مقاله به اهمیت انگیزش درونی پرداخته و نگاه کوتاهی به جایگاه آن در روان‌شناسی دارد. سپس تحقیقات پیرامون انگیزش درونی در هوش مصنوعی دسته‌بندی‌شده و مورد بررسی قرار گرفتهاند. همچنین، روش یادگیری تقویتی به‌عنوان رویکردی موفق در ترکیب انگیزش درونی بررسی شده است. در نهایت، به برخی از کاربردهای عملی انگیزش درونی، محدودیتها و تحقیقات آینده اشاره شده است.
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