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A Reinforcement Learning Technique For Enhancing Human Behavior Models In A Context-Based Architecture, David Aihe
A Reinforcement Learning Technique For Enhancing Human Behavior Models In A Context-Based Architecture, David Aihe
Electronic Theses and Dissertations
A reinforcement-learning technique for enhancing human behavior models in a context-based learning architecture is presented. Prior to the introduction of this technique, human models built and developed in a Context-Based reasoning framework lacked learning capabilities. As such, their performance and quality of behavior was always limited by what the subject matter expert whose knowledge is modeled was able to articulate or demonstrate. Results from experiments performed show that subject matter experts are prone to making errors and at times they lack information on situations that are inherently necessary for the human models to behave appropriately and optimally in those situations. …
An Adaptive Multiobjective Evolutionary Approach To Optimize Artmap Neural Networks, Assem Kaylani
An Adaptive Multiobjective Evolutionary Approach To Optimize Artmap Neural Networks, Assem Kaylani
Electronic Theses and Dissertations
This dissertation deals with the evolutionary optimization of ART neural network architectures. ART (adaptive resonance theory) was introduced by a Grossberg in 1976. In the last 20 years (1987-2007) a number of ART neural network architectures were introduced into the literature (Fuzzy ARTMAP (1992), Gaussian ARTMAP (1996 and 1997) and Ellipsoidal ARTMAP (2001)). In this dissertation, we focus on the evolutionary optimization of ART neural network architectures with the intent of optimizing the size and the generalization performance of the ART neural network. A number of researchers have focused on the evolutionary optimization of neural networks, but no research has …