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Spring 2024
This dissertation develops simple and practical learning algorithms from first principles for long-lived agents. Formally, the algorithms are developed within the reinforcement learning framework for continuing (non-episodic) problems, in which the agent-environment interaction goes on ad...
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Reinforcement Learning-enhanced Path Planning for Mobile Cranes in Dynamic Construction Environments: A Virtual Reality–Simulation Approach
DownloadFall 2024
This work presents a novel approach to constructing site crane path planning using reinforcement learning and virtual-reality simulations. The approach involves a comprehensive simulation model that includes an agent, actions, states, environment, and a reward system. After extensive training...
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Fall 2020
Research in artificial general intelligence aims to create agents that can learn from their own experience to solve arbitrary tasks in complex and dynamic settings. To do so effectively and efficiently, such an agent must be able to predict how its environment will change both dependently and...
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Fall 2023
Learning only by direct interaction with the world can be expensive in many real world applications. In such settings, Model-based Reinforcement Learning (MBRL) methods are a promising avenue towards data-efficiency. By planning with a model, a sequential decision making agent can decrease its...
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Fall 2020
High stress levels and depression are commonly observed in hospitalized patients, which may negatively impact them on recovery after surgery. Sound therapy has been widely used for its effectiveness in increasing relaxation and reducing stress levels, and one could also fine-tune music features...
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Fall 2023
Monoclonal antibodies (mAbs) have become indispensable assets in modern medicine, necessitating advancements in large-scale production to meet the growing market demand. This thesis focuses on two critical aspects of mAb production: state estimation in the upstream process and the control and...
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Fall 2018
Dyna is an architecture for reinforcement learning agents that interleaves planning, acting, and learning in an online setting. This architecture aims to make fuller use of limited experience to achieve better performance with fewer environmental interactions. Dyna has been well studied in...