A naturalistic account of the strengths and limitations of cladistic practice is offered. The success of cladistics is claimed to be largely rooted in the parsimony-implementing congruence test. Cladists may use the congruence test to iteratively refine assessments of homology, and thereby increase the odds of reliable phylogenetic inference under parsimony. This explanation challenges alternat...

Soft computing (SC) is an association of computing methodologies that includes as its principal members fuzzy logic, neurocomputing, evolutionary computing and probabilistic computing. We present a collection of methods and tools that can be used to perform diagnostics, estimation, and control. These tools are a great match for real-world applications that are characterized by imprecise, uncert...

Problem domain information extraction is a critical issue in many real-world optimization problems. Increasing the repertoire of techniques available in evolutionary algorithms with this purpose is fundamental for extending the applicability of these algorithms. In this paper we introduce a unifying information mining approach for evolutionary algorithms. Our proposal is based on a division of ...

We use molecular computation to solve pattern classification problems. DNA molecules encode data items and the DNA library represents the empirical probability distribution of data. Molecular bio-lab operations are used to compute conditional probabilities that decide the class label. This probabilistic computational model distinguishes itself from the conventional DNA computing models in that ...

Three main streams of Evolutionary Algorithms (EAs), i.e. probabilistic optimization algorithms based on the model of natural evolution, are compared with each other in this article: Evolution Strategies (ESs), Evolutionary Programming (EP), and Genetic Algorithms (GAs). The comparison is performed with respect to certain characteristic components of EAs, i.e. the representation scheme of objec...

SUMMARY Count is a software package for the analysis of numerical profiles on a phylogeny. It is primarily designed to deal with profiles derived from the phyletic distribution of homologous gene families, but is suited to study any other integer-valued evolutionary characters. Count performs ancestral reconstruction, and infers family- and lineage-specific characteristics along the evolutionar...

Recently many researchers have studied the estimation of distribution algorithms (EDAs) as an optimization method. While most EDAs focus on solving combinatorial optimization problems, only a few algorithms have been proposed for continuous function optimization. In previous work, we developed a Bayesian evolutionary algorithm (BEA) for combinatorial optimization problem using a probabilistic g...

The notion that phenotypic traits, including behavior, can be predetermined has slowly given way in biology and psychology over the last two decades. This shift in thinking is due in large part to the growing evidence for the fundamental role of developmental processes in the generation of the stability and variations in phenotype that researchers in developmental and evolutionary sciences seek...

Fractal Image Compression is a well-known problem which is in the class of NP-Hard problems. Quantum Evolutionary Algorithm is a novel optimization algorithm which uses a probabilistic representation for solutions and is highly suitable for combinatorial problems like Knapsack problem. Genetic algorithms are widely used for fractal image compression problems, but QEA is not used for this kind o...