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- 17Machine Learning
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- 1Abbasi Brujeni, Lena
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Chasing Hallucinated Value: A Pitfall of Dyna Style Algorithms with Imperfect Environment Models
DownloadSpring 2020
In Dyna style algorithms, reinforcement learning (RL) agents use a model of the environment to generate simulated experience. By updating on this simulated experience, Dyna style algorithms allow agents to potentially learn control policies in fewer environment interactions than agents that use...
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Fall 2023
Off-policy policy evaluation has been a critical and challenging problem in reinforcement learning, and Temporal-Difference (TD) learning is one of the most important approaches for addressing it. There has been significant interest in searching for off-policy TD algorithms which find the same...
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Fall 2021
Learning auxiliary tasks, such as multiple predictions about the world, can provide many benets to reinforcement learning systems. A variety of off-policy learning algorithms have been developed to learn such predictions, but as yet there is little work on how to adapt the behavior to gather...
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Fall 2023
Multilevel action selection is a reinforcement learning technique in which an action is broken into two parts, the type and the parameters. When using multilevel action selection in reinforcement learning, one must break the action space into multiple subsets. These subsets are typically disjoint...
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Fall 2016
Current medical imaging professional training uses an apprenticeship model with students following an established doctor and viewing their cases, in what is called a practicum. This posses an issue as students are limited to the cases available during their practicum. To resolve this automated...
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Data-Driven and Artificial Intelligence Approach to Dynamic Truck Fleet Dispatching and Shovel Allocation Planning in Open-Pit Mines
DownloadFall 2023
An open-pit mine is a highly dynamic environment where different equipment resources are allocated to mining areas to extract metal-bearing rock and waste, for pit development, following a set flow of activities. The material mined is then transported through the mine road network to different...
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Spring 2024
Retrofitting buildings and optimizing their operation have been at the forefront of global efforts to reduce carbon emissions over the past few decades. Intelligent control of building systems, such as Heating, Ventilation, and Air Conditioning (HVAC), presents two clear benefits: it improves...
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Decision Frequency Adaptation in Reinforcement Learning Using Continuous Options with Open-Loop Policies
DownloadFall 2023
In classic reinforcement learning(RL) for continuous control, agents make decisions at discrete and fixed time intervals. The duration between decisions becomes a crucial hyperparameter. Setting it too short may increase the problem’s difficulty by requiring the agent to make numerous decisions...
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Design and Optimal Operation of a Virtual Power Plant with Bidirectional Electric Vehicle Chargers
DownloadSpring 2023
Virtual power plants (VPPs) can enhance reliability and efficiency of power systems with a high share of renewables. However, their adoption largely depends on their profitability, which is difficult to maximize due to the heterogeneity of their components, different sources of uncertainty and...