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Spring 2024

Costello, Jeremy

We introduce the background of the natural language processing field, outlining the benefits and drawbacks of rule-based versus statistical methods. We present knowledge graphs as a way to integrate the explainability of rule-based methods and the power of statistical methods, large language...

Fall 2023

Wan, Yi

The average-reward formulation is a natural and important formulation of learning and planning problems, yet has received much less attention than the episodic and discounted formulations. This dissertation makes three areas of contributions to algorithms and their theories concerning the...

Spring 2023

Orfanos, Spyros

Oblique decision trees use linear combinations of features in the decision nodes. Due to the non-smooth structure of decision trees, training oblique decision trees is considerably difficult as the parameters are tuned using expensive non-differentiable optimization techniques or found by...

Fall 2024

Parker, Adam SR

Modern myoelectric artificial limbs are sophisticated devices with many of the degrees of freedom of biological limbs. These devices have great potential to provide function for people with amputations, assisting them in participating in a greater number of activities and tasks of daily...

Spring 2019

Young, Kenneth

In realistic environments, intelligent agents must learn to integrate information from their past to inform present decisions. An agent's immediate observations are often limited, and some degree of memory is necessary to complete many everyday tasks. However, an agent cannot remember everything...

Fall 2023

Kearney, Alexandra K

Of all the capabilities of natural intelligence, one of the most exceptional is the ability to expand upon and refine knowledge of the world through subjective experience. Therefore, a longstanding goal of Artificial Intelligence has been to replicate this success: to enable artificial agents to...

Fall 2024

Sadmine, Quazi Asif

Despite having advantages such as generalizability and interpretability over neural representations, programmatic representations of hypotheses and strategies face significant challenges. This is because algorithms writing programs encoding hypotheses for solving supervised learning problems and...

Fall 2023

Schlegel, Matthew K

Partial observability---when the senses lack enough detail to make an optimal decision---is the reality of any decision making agent acting in the real world. While an agent could be made to make due with its available senses, taking advantage of the history of senses can provide more context and...

2011

Yao, Hengshuai

Technical report TR11-04. World model is very important for model-based reinforcement learning. For example, a model is frequently used in Dyna: in learning steps to select actions and in planning steps to project sampled states or features. In this paper we propose least-squares Dyna (LS-Dyna)...

Fall 2021

Kamyab, Majid

Unmanned Aerial Vehicles (UAVs), or drones, have been employed in a variety of applications, ranging from surveillance to emergency operations. These systems comprise an ”inner loop” that provides stability and control and an ”outer loop” in charge of mission-level tasks, such as way-point...