IMPLEMENTATION OF BOLTZMANN MACHINE IN NEURO-SYMBOLIC INTEGRATION
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Date
2010-04
Authors
TEOH, YEONG KIN
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Abstract
In this dissertation, we present and compare two methods of doing logic
program on a Hopfield network based on the energy minimization scheme. The
proposed method is based on the Boltzmann Machine model. Computer simulations
to demonstrate the ability of Boltzmann Machine doing logic program on a Hopfield
network will be discussed. Besides that, global minima ratio of network programmed
by program clauses in the features of running time and complexity are also been
analyzed. Program experiments were conducted using Microsoft Basic C 6.0
software. The present study shows that the Boltzmann Machine model is more stable
and efficient. Given a sufficient time, Boltzmann Machine is able to represent and
solve difficult combinatory problems.
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Keywords
IMPLEMENTATION , SYMBOLIC