But the one-locus model illustrates the essence of population-genetic reasoning, and the attendant clarification of the evolutionary process that it brings.
As we have seen, population-genetic reasoning assumes that an organism's genes somehow affect its phenotype, and thus its fitness, but it is silent about the details of how genes actually build organisms, i.e. about embryology.
For example, the well-known 'gene's eye' view of evolution, developed by biologists such as G.C. Williams, W.D. Hamilton and Richard Dawkins, stems directly from population-genetic reasoning; indeed, important aspects of gene's eye thinking were already present in Fisher's writings (Okasha 2008).
In this paper, a hybrid approach, case-based reasoning genetic algorithm (CBR-GA) is applied to the soccer game for providing better strategies.
A multi-agent learning system, constructed by combining case-based reasoning genetic algorithm with RBR strategy (CGRS), is implemented on the latest WrightEagle simulation platform that is released in 2011.
It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc).
Instead, we need to complement the conventional analysis methods with a number of emerging methodologies and soft computing techniques such as expert systems, artificial intelligence, neural network, fuzzy logic, genetic algorithm, probabilistic reasoning, and parallel processing techniques.
"They have very sophisticated interpretations that are based on statistical, genetic, and historical reasoning," Panofsky said.
For the second level, a genetic algorithm (GA) based reasoning and an RNN based learning has been developed.
The study includes the following paradigms; artificial neural networks, fuzzy logic, genetic algorithms, case-based reasoning, support vector machines, and swarm intelligence.
To model the second framework, we developed a hybrid cognitive engine (CE) architecture by integrating an RNN based learning algorithm with genetic algorithm (GA) based reasoning.
