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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...

Spring 2010

Tom, David

The Monte-Carlo Tree Search (MCTS) algorithm Upper Confidence bounds applied to Trees (UCT) has become extremely popular in computer games research. Because of the importance of this family of algorithms, a deeper understanding of when and how their different enhancements work is desirable. To...

Fall 2015

Poo Hernandez, Sergio

Artificial Intelligence (AI) techniques have been widely used in video games to control non-playable characters. More recently, AI has been applied to automated story generation with the objective of managing the player’s experience in an interactive narrative. Such AI experience managers can...

Fall 2020

Luan, Yixing

Word sense disambiguation (WSD) is one of the core tasks in natural language processing and its objective is to identify the sense of a content word (nouns, verbs, adjectives, and adverbs) in context, given a predefined sense inventory. Although WSD is a monolingual task, it has been conjectured...

Spring 2023

Ashrafi Asli, Seyed Arad

With machine learning models becoming more complicated and more widely applied to solve real-world challenges, there comes the need to explain their reasoning. In parallel with the advancements of deep learning methods, Explainable AI (XAI) algorithms have been proposed to address the issue of...

Spring 2019

Stanescu, Adrian M

For many years, traditional boardgames such as Chess, Checkers or Go havebeen the standard environments to test new Artificial Intelligence (AI) algorithms for achieving robust game-playing agents capable of defeating the best human players. Presently, the focus has shifted...

Fall 2011

Metcalf, Adam

Pinball is fast-paced arcade-style game of which the origins date back hundreds of years. Game playing robots exist for billiards, foosball, and soccer and each have their own unique challenges. The speed that balls move in pinball machines requires that players have quick reactions. We created...

Fall 2023

Krishna Guruvayur Sasikumar, Aakash

The application of reinforcement learning (RL) to the optimal control of building systems has gained traction in recent years as it can reduce building energy consumption and improve human comfort, without requiring the knowledge of the building model. However, existing RL solutions for building...

Fall 2016

Liu, Yifeng

The field of biomedicine is reeling from “information overload”. Indeed, biomedical researchers find it almost impossible to stay current with published literature due to the vast amounts of data being generated and published. As a result, they are turning to text mining. Over the past two...

Spring 2016

Johanson, Michael Bradley

Games have been used as a testbed for artificial intelligence research since the earliest conceptions of computing itself. The twin goals of defeating human professional players at games, and of solving games outright by creating an optimal computer agent, have helped to drive practical ...