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Fall 2019

Mathewson, Kory W.

Improvisation is a form of live theatre where artists perform real-time, dynamic problem solving to collaboratively generate interesting narratives. The main contribution of this thesis is the development of artificial improvisation: improvised theatre performed by humans alongside intelligent...

Fall 2017

Zhang, Shuyi

Modern board, card, and video games are challenging domains for AI research due to their complex game mechanics and large state and action spaces. For instance, in Hearthstone — a popular collectible card (CC) (video) game developed by Blizzard Entertainment — two players first construct their...

Spring 2024

Patterson, Andrew

In this thesis, we seek to improve the reliability of reinforcement learning algorithms for nonlinear function approximation. Semi-gradient temporal difference (TD) update rules form the basis of most state-of-the-art value function learning systems despite clear counterexamples proving their...

Spring 2022

Saha, Rohan

Infants start developing rudimentary language skills and can start understanding simple words well before their first birthday. This development has also been shown primarily using Event Related Potential (ERP) techniques to find evidence of word comprehension in the infant brain. While these...

Spring 2021

Wong, Andy

This thesis investigates the use of general value functions for detecting anomalous behavior in machines. Identifying abnormal behavior is critical for ensuring the safety and reliability of any machine or industrial process. When the cause of these anomalies is due to accumulated wear on...

Spring 2020

Sara Soltaninejad

Parkinson's disease (PD) is the second major neuro-degenerative disorder caused by dopaminergic loss in the brain region known as the Substantia Nigra (SN). The major symptoms of this disease are motor and non-motor abnormalities, which may show at early stages of PD. Physical exam, demographic...

Fall 2020

Chockalingam, Valliappa

The reinforcement learning framework provides a simple way to study computational intelligence as the interaction between an agent and an environment. The goal of an agent is to accrue as much reward as possible by intelligently choosing actions given states. This problem of finding a policy that...

Fall 2024

Mirgati, Seyyede Negar

Procedural Content Generation via Machine Learning (PCGML) faces a significant hurdle that sets it apart from other ML problems, such as image or text generation, which is limited annotated data. For example, many existing methods for level generation via machine learning specifically require a...

Spring 2011

Lin, Hsiu-Chin

Standard survival analysis focuses on population-based studies. The objective of our work, survival prediction, is different: to find the most accurate model for predicting the survival times for each individual patient. We view this as a regression problem, where we try to map the features for...

Fall 2013

Kiros, Ryan J

Significant research has gone into engineering representations that can identify high-level semantic structure in images, such as objects, people, events and scenes. Recently there has been a shift towards learning representations of images either on top of dense features or directly from the...