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University of Central Florida

Electronic Theses and Dissertations

Neural Networks

Publication Year

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Full-Text Articles in Computer Engineering

Falconet: Force-Feedback Approach For Learning From Coaching And Observation Using Natural And Experiential Training, Gary Stein Jan 2009

Falconet: Force-Feedback Approach For Learning From Coaching And Observation Using Natural And Experiential Training, Gary Stein

Electronic Theses and Dissertations

Building an intelligent agent model from scratch is a difficult task. Thus, it would be preferable to have an automated process perform this task. There have been many manual and automatic techniques, however, each of these has various issues with obtaining, organizing, or making use of the data. Additionally, it can be difficult to get perfect data or, once the data is obtained, impractical to get a human subject to explain why some action was performed. Because of these problems, machine learning from observation emerged to produce agent models based on observational data. Learning from observation uses unobtrusive and purely …


Learning Human Behavior From Observation For Gaming Applications, Christopher Moriarty Jan 2007

Learning Human Behavior From Observation For Gaming Applications, Christopher Moriarty

Electronic Theses and Dissertations

The gaming industry has reached a point where improving graphics has only a small effect on how much a player will enjoy a game. One focus has turned to adding more humanlike characteristics into computer game agents. Machine learning techniques are being used scarcely in games, although they do offer powerful means for creating humanlike behaviors in agents. The first person shooter (FPS), Quake 2, is an open source game that offers a multi-agent environment to create game agents (bots) in. This work attempts to combine neural networks with a modeling paradigm known as context based reasoning (CxBR) to create …


Genetically Engineered Adaptive Resonance Theory (Art) Neural Network Architectures, Ahmad Al-Daraiseh Jan 2006

Genetically Engineered Adaptive Resonance Theory (Art) Neural Network Architectures, Ahmad Al-Daraiseh

Electronic Theses and Dissertations

Fuzzy ARTMAP (FAM) is currently considered to be one of the premier neural network architectures in solving classification problems. One of the limitations of Fuzzy ARTMAP that has been extensively reported in the literature is the category proliferation problem. That is Fuzzy ARTMAP has the tendency of increasing its network size, as it is confronted with more and more data, especially if the data is of noisy and/or overlapping nature. To remedy this problem a number of researchers have designed modifications to the training phase of Fuzzy ARTMAP that had the beneficial effect of reducing this phenomenon. In this thesis …