Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management

Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management

A Master of Science thesis in Computer Engineering by Mohammed Omer Alamin Alhusin entitled, “Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management”, submitted in December 2019. Thesis advisor is Dr. Michel Pasquier and thesis co-advisor is Dr. Gerassimos Barlas. Soft copy is a...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Alhusin, Mohammed Omer Alamin (author)
التنسيق: doctoralThesis
منشور في: 2019
الموضوعات:
Markov Decision Process
Markov Game
Deep Learning
Multi-Agent Reinforcement Learning
Convolutional Neural Network
Fleet Management
Taxi Dispatch Problem
الوصول للمادة أونلاين:http://hdl.handle.net/11073/16577
الوسوم: إضافة وسم
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الوصف
الملخص:A Master of Science thesis in Computer Engineering by Mohammed Omer Alamin Alhusin entitled, “Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management”, submitted in December 2019. Thesis advisor is Dr. Michel Pasquier and thesis co-advisor is Dr. Gerassimos Barlas. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).

مواد مشابهة