Improving single and multi-agent deep reinforcement learning methods

Thesis

Reinforcement Learning (RL) is a framework where an agent learns to make decisions using data-driven feedback from interactions with the environment in the form of rewards or penalties for actions. Deep RL integrates deep learning with RL, harnessing the power of deep neural networks to process complex, high-dimensional data. Using the framework of deep RL, our machine learning research community has achieved tremendous progress in enabling machines to make sequential decisions over long t...

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Authors: Gupta, T

• DOI: 10.5287/ora-gowder4np
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: deep learning; reinforcement learning; exploration; multi-agent; foundation models
• Subjects: Machine learning