Index Catalog // ScholarsArchive@OSU

Bayesian methods for knowledge transfer and policy search in reinforcement learning

Creator:: Wilson, Aaron
Abstract:: How can an agent generalize its knowledge to new circumstances? To learn effectively an agent acting in a sequential decision problem must make intelligent action selection choices based on its available knowledge. This dissertation focuses on Bayesian methods of representing learned knowledge and develops novel algorithms that exploit the represented...
Resource Type:: Dissertation

Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

Creator:: Raghavan, Aswin
Abstract:: Markov Decision Processes (MDPs) are the de-facto formalism for studying sequential decision making problems with uncertainty, ranging from classical problems such as inventory control and path planning, to more complex problems such as reservoir control under rainfall uncertainty and emergency response optimization for fire and medical emergencies. Most prior research...
Resource Type:: Dissertation
Full Text:: thankful to Carl Neidner and Coelo Company of Design for providing the dataset of emergencies that oc

High-Dimensional Reinforcement Learning with Human Feedback

Creator:: Curran, William
Abstract:: State-of-the-art personal robots need to perform complex manipulation tasks to be viable in complex scenarios. However, many of these robots, like the PR2, use manipulators with high degrees of freedom. High degrees of freedom are desirable from a functionality standpoint, but make the learning task more difficult by adding a...
Resource Type:: Dissertation

Simulator-Defined MDP Planning with Applications in Natural Resource Management

Creator:: Alkaee Taleghan, Majid
Abstract:: This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
Resource Type:: Dissertation
Full Text:: throughout my graduate studies. Special thanks to Sean McGregor, Liping Liu, Jesse Hostetler, and Shahed

Machine Learning Techniques to Model Species Interactions and Distributions Under Imperfect Detection

Creator:: Seo, Eugene
Abstract:: Ecological domains seeking to understand the environment and the behavior of species have received little attention in machine learning (ML), despite the fact that environmental changes have a significant impact on humans as well as ecosystems. Some ecological problems can be formulated similarly to other common ML applications, but there...
Resource Type:: Dissertation

Learning and Improving Policies for Probabilistic Planning Problems

Creator:: Issakkimuthu, Murugeswari
Abstract:: In this work, we study the problem of learning and improving policies for probabilistic planning problems. In the first part, we train neural network policies for probabilistic planning problems modeled as factored Markov decision problems. The objective is to train problem-specific neural networks via supervised learning to imitate the action...
Resource Type:: Dissertation

Investigating Latent State and Uncertainty Representations in Reinforcement Learning

Creator:: Koul, Anurag
Abstract:: Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
Resource Type:: Dissertation

Inclusive Software Design and Its Methods for Beyond-WIMP User Interfaces

Creator:: Fallatah, Abrar
Abstract:: While digital inclusivity researchers and software practitioners have been trying to address exclusion biases in Windows, Icons, Menus, and Pointers (WIMP) user interfaces (UIs) for a long time, little has been done to investigate if and how inclusive software design and its methods that have been devised for WIMP UIs...
Resource Type:: Dissertation

Semantic embodied navigation : developing agents that navigate from language and vision

Creator:: Krantz, Jacob
Abstract:: Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Resource Type:: Dissertation
Full Text:: collaborations and Peter Anderson and Jesse Thomason for their advising insights and generosity. I thank the

ScholarsArchive@OSU

Bayesian methods for knowledge transfer and policy search in reinforcement learning

Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

High-Dimensional Reinforcement Learning with Human Feedback

Simulator-Defined MDP Planning with Applications in Natural Resource Management

Machine Learning Techniques to Model Species Interactions and Distributions Under Imperfect Detection

Learning and Improving Policies for Probabilistic Planning Problems

Investigating Latent State and Uncertainty Representations in Reinforcement Learning

Inclusive Software Design and Its Methods for Beyond-WIMP User Interfaces

Semantic embodied navigation : developing agents that navigate from language and vision

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