پديد آورنده :
حسن پورآده، داريوش
عنوان :
بهبود كيفيت و سرعت يادگيري در سيستم هاي چند عامله با استفاده از معيار جديد خبرگي و انتگرال فازي
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
هوش مصنوعي و رباتيك
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر
صفحه شمار :
سيزده، 80ص.: مصور، جدول، نمودار
يادداشت :
ص. ع. به فارسي و انگليسي
استاد راهنما :
مازيار پالهنگ
توصيفگر ها :
سيستم هاي چند عامله , يادگيري مشاركتي , يادگيري تقويتي , دانش غير افزايشي , انتگرال فازي
استاد داور :
عبدالرضا ميرزايي، محمدحسين منشئي
تاريخ ورود اطلاعات :
1396/02/16
رشته تحصيلي :
برق و كامپيوتر
دانشكده :
مهندسي برق و كامپيوتر
چكيده انگليسي :
Improvments in speed and quality of learning in multi agent systems using a novel expertness criteria and fuzzy integral Dariush Hasanpour Adeh d hasanpoor@ec iut ac ir Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Assoc Prof Maziar Palhang palhang@cc iut ac ir Abstract In the real world usually peoples are coming together for sharing their knowledge and talkingfrom their good and bad experiences and more or less everybody has something to say Although wecannot ignore anybody s knowledge but it s common sense to assign more weight on the most expe rienced person s knowledge when we are going to decide what we need to do based on consultationfrom people The achievements of this research have the same philosophy that everybody needs tobe heard Fuzzy integrals are one of the most powerful and flexible methods for hearing everybody sknowledge and extract knowledge which is useful for everybody One of the challenges is that how to fairly answer the what is the agents expertise and how todetermine the most and least expert agent question To answer this question in this thesis we haveproposed the hypothesis of expertness which defines a framework for expertness criteria defi nitions and based on this framework we have introduced a new expertness criteria and showed thatthe defined framework and criteria are much more efficient than the state of the art criteria ShortestExperienced Path criteria Also the power of using fuzzy integrals for intelligence aggregation andnon additive measuring knowledge is demonstrated Key Words Multi agent Systems Cooperative Learning Reinforcement Learning Fuzzy Integral Non additiveKnowledge
استاد راهنما :
مازيار پالهنگ
استاد داور :
عبدالرضا ميرزايي، محمدحسين منشئي
