Game-theoretic payoff allocation in multiagent machine learning systems

Thesis

Machine learning (ML) is becoming ubiquitous in real-world applications, spanning from our domestic devices such as vacuum cleaner robots, smart phones, virtual assistants, to industrial applications such as manipulators, warehouse robots, to public services such as medical imaging, surveillance cameras, energy grid, etc. With the growing ubiquity and interconnection of these devices, interactions among them will soon become commonplace. These emerging ML problems and the interactions amon...

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Authors: Han, D

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: Multiagent Systems; Cooperative Game Theory; Semivalue; Reinforcement Learning
• Subjects: Reinforcement learning; Multiagent systems; Cooperative games (Mathematics)