Extended Compact Genetic Algorithm in Matlab
Sastry, K. Orriols-Puig, A. (2007)TR No.: 2007009 | Download PDF | Download PS
Abstract:
This report provides documentation for matlab® implementation of the extended compact genetic algorithm (eCGA). The implementation works for integer decision variables where each variable can be of differing cardinality.
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Posted: February 16th, 2007 under Genetic algorithms. Comments: none
Analyzing Probabilistic Models in Hierarchical BOA on Traps and Spin Glasses
Hauschild, M., Pelikan, M., Lima, C. F., Sastry, K. (2007)TR No.: 2007008 | Download PDF | Download PS
Abstract:
The hierarchical Bayesian optimization algorithm (hBOA) can solve nearly decomposable and hierarchical problems of bounded difficulty in a robust and scalable manner by building and sampling probabilistic models of promising solutions. This paper analyzes probabilistic models in hBOA on two common test problems: concatenated traps and 2D Ising spin glasses with periodic boundary conditions. We […]
Posted: February 12th, 2007 under Genetic algorithms. Comments: none
Towards Billion Bit Optimization via Efficient Genetic Algorithms
Sastry, K., Goldberg, D. E., Llorà, X. (2007)TR No.: 2007007 | Download PDF | Download PS
Abstract:
This paper presents a highly efficient, fully parallelized implementation of the compact genetic algorithm to solve very large scale problems with millions to billions of variables. The paper presents principled results demonstrating the scalable solution of a difficult test function on instances over a billion variables using a parallel implementation of compact genetic algorithm (cGA). […]
Posted: February 8th, 2007 under Genetic algorithms. Comments: none
Towards Better than Human Capability in Diagnosing Prostate Cancer Using Infrared Spectroscopic Imaging
Llorà, X., Reddy, R., Matesic, B., Bhargava, R. (2007)TR No.: 2007006 | Download PDF | Download PS
Abstract:
Cancer diagnosis is essentially a human task.
Almost universally, the process requires the
extraction of a piece of tissue and examination of a
microstructure by a human. A new approach has
been proposed that uses molecular spectroscopic
imaging, instead, and examines the chemical
properties instead for diagnoses. In contrast to
visible imaging, the approach results in very large
data sets as each pixel […]
Posted: February 4th, 2007 under Genetic algorithms. Comments: none
Let’s Get Ready to Rumble Redux: Crossover Versus Mutation Head to Head on Exponentially Scaled Problems
Sastry, K., Goldberg, D. E. (2007)TR No.: 2007005 | Download PDF | Download PS
Abstract:
This paper analyzes the relative advantages between crossover and mutation on a class of deterministic and stochastic additively separable problems with substructures of non-uniform salience. This study assumes that the recombination and mutation operators have the knowledge of the building blocks (BBs) and effectively exchange or search among competing BBs. Facetwise models of convergence time […]
Posted: January 24th, 2007 under Genetic algorithms. Comments: none
Modeling Selection Pressure in XCS for Proportionate and Tournament Selection
Orriols-Puig, A., Sastry, K., Lanzi, P. L., Goldberg, D. E., Bernadó-Mansilla, E. (2007)TR No.: 2007004 | Download PDF | Download PS
Abstract:
In this paper, we derive models of the selection pressure in XCS for proportionate (roulette wheel) selection and tournament selection. We show that these models can explain the empirical results that have been previously presented in the literature. We validate the models on simple problems showing that, (i) when the model assumptions hold, the theory […]
Posted: January 20th, 2007 under Genetic algorithms. Comments: none
Empirical Analysis of Generalization and Learning in XCS with Gradient Descent
Lanzi P.L., Butz M.V., Goldberg, D.E., (2007)TR No.: 2007003 | Download PDF | Download PS
Abstract:
We analyze generalization and learning in XCS with gradient descent. At
first, we show that the addition of gradient in XCS may slow down
learning because it indirectly decreases the learning rate. However, in
contrast to what was suggested elsewhere, gradient descent has no effect
on the achieved generalization. We also show that when gradient descent
is combined with roulette […]
Posted: January 16th, 2007 under Genetic algorithms. Comments: none
Classifier Systems that Compute Action Mappings
Lanzi, P.L., Loiacono D. (2007)TR No.: 2007002 | Download PDF | Download PS
Abstract:
The learning complexity of niche based learning classifier systems
depends both on the complexity of the problem state space and on the
number of available actions. In this paper, we introduce a version of
XCS with computed actions, briefly XCSCA, that can be applied to
problems involving a large number of actions. We report experimental
results showing that XCSCA can […]
Posted: January 12th, 2007 under Genetic algorithms. Comments: none
Modeling XCS in Class Imbalances: Population Size and Parameter Settings
Orriols-Puig, A., Goldberg, D. E., Sastry, K., Bernadó-Mansilla, E. (2007)TR No.: 2007001 | Download PDF | Download PS
Abstract:
This paper analyzes the scalability of the population size required in XCS to maintain niches that are infrequently activated. Facetwise models have been developed to predict the effect of the imbalance ratio—ratio between the number of instances of the majority class and the minority class that are sampled to XCS—on population initialization, and on the […]
Posted: January 8th, 2007 under Genetic algorithms. Comments: none