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Autoencoder Guided Estimation of Distribution Algorithm

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  • Tue, 10/10/2017 - 1:00pm - 3:00pm




Autoencoder Guided

 Estimation of Distribution Algorithm

PhD. Thesis Proposal by:

Sourodeep Bhattacharjee

Date: Tuesday, October 10, 2017
Time:1:00 pm - 3:00 pm
Location: 3105, Lambton Tower

Abstract: The proposed research involves use of Auto-Encoders (AE) for population model building in Estimation of Distribution Algorithm (EDA). A Self Denoising Auto-Encoder (DAE-EDA) would also be incorporated in the study, hence making the combinatorial optimizers robust to intrinsic noise. As an application of DAE-EDA we propose a Wrapper method extending DAE-EDA with C4.5 decision trees and apply it to make predictions in the domain of EcoSim.

We propose to study Communication of Fear in prey individuals in presence of predators in EcoSim. Although receivers are given the ability to perceive the communication from signallers, there is no explicit model of how this signal is used. The objective here is to observe how the prey uses the information to improve fitness. In another study with EcoSim we have modeled Sexual Selection in which the female individuals employ an elitist strategy when selecting mates. In this research we will compare the effect of Sexual Selection on Speciation and Extinction rates and contrast the results with random mate selection.

Thesis Committee:     

Internal Reader:          Dr. Boubakeur Boufama
Internal Reader:          Dr. Imran Ahmad
External Reader:         Dr. Ken Drouillard
Advisor:                      Dr. Robin Gras

 

 



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