2 Evolutionary Computation Algorithms
2.1 Introduction
Evolutionary computation algorithms are based on the biology evolution theory. Have you ever heard the phrase "Survival of the fittest" - Herbert Spencer? Imagine an island of castaways and the only resource of food are coconut trees. It make sense that whoever is tall enough will feed and survive. A few years after those people will match and give birth to children with better characteristics, in our case taller. So as the years gone by and generations comes and go the island will end up with almost only tall people.
Based on the evolutionary theory as described above, evolutionary computation produce solutions and keeping the fittest of them. In 1948, Alan Turing was the first who introduce this biological approach in problem solving. On 1962, we had the first actual experiments on "optimization through evolution and recombination".
Below I will analyse the most important components of an evolutionary computation algorithm and explain how it works.
2.2 Representation
Let us see now how this algorithm works. The algorithms randomly creates solutions. Each one of these solutions has a fitness value based on some criteria. Those solutions of a specific problem are also called Phenotype, while the encoding of each solution is called Genotype. We refer on Representation as the procedure of establish the mapping between genotypes and phenotypes. Representation is used as in two different ways. As mentioned before, representation establish the mapping between the genotype and the phenotype. This means that representation could encode ore decode the candidate solutions.
2.3 Fitness or Evaluation Function
Evaluation function or as is commonly referred the fitness function i...
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...ly into the new population. We repeated this procedure until the termination condition is matched.
Termination condition is the condition that ends the evolutionary computation cycles. Termination condition can be the maximum number of cycles allowed, ore in case we know the optimal solution the value of that solution.
2.8.2 Stages of the Algorithm
As the generations come and go the individuals in the population will become of better quality and the best of them will become even better. As present in the diagram below.
Let us now see the quality of individual the population over the time. As shown below at the starting point of the algorithm individuals are of less quality. However as the time goes by population’s individuals are getting of higher quality and reaching the pick of global and local optima. The image below illustrate these stages of the algorithm.
Biological evolution is a change in the characteristics of living organisms over generations (Scott, 2017). A basic mechanism of evolution, the genetic drift, and mutation is natural selection. According to Darwin's theory of evolution, natural selection is a process in nature in which only the organisms best adapted to their environmental surroundings have a higher chance of surviving and transmitting their genetic characters in increasing numbers to succeeding generations while those less adapted tend to be eliminated. There has been many experimental research projects that relate to the topic of natural selection and evolution.
The simulator does something similar to this. The organisms in the beginning are identical. They have arms of a similar length as a result of their phenotypes. To simulate nature, every cycle we could say represents a generation. Every generation we see new organisms born with random mutations. Based on the environment we see different mutations on the newborn. For example, if its environment through the generations allowed its ancestors to survive, based on the phenotypes we saw in the ancestors we can see them again in the newborn. Basically saying that the parents of the newborn lived long enough to mate with the same traits., in turn giving the newborn those same exact traits. In this case, it is traits which code for arms length.
What is evolution? Evolution in modern terms is fairly easy to understand. Evolution is the theory that life on earth began with a single celled organism that lived more that 3.5 billion years ago that slowly evolved into many diverse creatures over time. When you break down this theory into sections you get 6 factors: evolution, gradualism, speciation, common ancestry, natural selection and nonselective mechanisms of evolutionary change.
Evolution in general, is a hard concept to grasp. There are multiple factors that effect the outcome a species, for example: genetics, nurture, nature, and the environment all play an important role. It was once said that species do not survive due to the fact that they are the strongest or the most intelligent, but because that species is the most responsive to change.
This evolution theory is the main idea of the exhibit we visited for our Independent Assignment. Here at the museum you are to learn about what the earth looked like billions of years ago and how did humans and other species living on this planet change to what we see today. How mankind came from a single cell and became the men walking among the earth today. In this paper the explanation and elaboration on what the idea of evolution is, where the idea came from, and how it has affected earth though out time.
It seems to be that the previous generation always picks on the new one. It’s something that’s been going on for decades, with the cry of “When I was your age!” at the tip of every adult’s tongue when they see the slightest bit of laziness or incompetence. In reality, each new generation brings waves of progress and innovation, built on top of the old. In this respect, it’s because every generation has the duty to do better than the last. Each generation needs to be bigger, greater, and bolder but this proves to be a challenge after countless centuries of people accomplishing the very same task. However, this problem can be simply solved by breaking the components down into the individual level. People just need to stay true to themselves and the rest will follow. Of course as Andrew Solomon 's Son and Lelie Bell’s Hard to Get demonstrate, creating an identity is much easier said than done. People have an obligation to be better than the previous generation and accomplish this by discovering who they are and then staying true to themselves.
Genetic Algorithms provide a holistic search process based on principles of natural genetics and survivals of the fittest……
Artificial intelligence folklore has been traced back to the times of Ancient Egypt. But the "birth of artificial intelligence" as some would call it, was in 1956 at the Dartmouth conference. The conference was based on two theories, the principle of feedback theory and the Logic Theorist. The principle of feedback theory was observed by Norbert Wiener. He theorized that all intelligent behavior was the result of a feedback mechanism. An example would be a temperature control system that simply checks the temperature of the room, compares the reading to the desired temperature, and adjusts the flow of heat to bring the room to the desired temperature. Then in 1955, Newell and Simon developed The Logic Theorist. The Logic Theorist was a program that represented every problem as a tree. The program would attempt to solve a problem by selecting the branch that would most likely result in the correct solution. Then in 1956, John McCarthy1 organized the Dartmouth Conference to draw interest and talent to the field of artificial intelligence.2
Darwin writes on how a species will adapt to its environment given enough time. When an animal gains a genetic edge over its competitors, be they of the same species or of another genus altogether, the animal has increased its chance of either procreation or adaptation. When this animal has this beneficial variance, the advantage becomes his and because of this, the trait is then passed on to the animals offspring.
The evolutionary theory is the concept that species evolve over time through the mechanism of natural selection of survival and reproduction. Natural selection means acting on the assumption that various living organisms were produced by genetic diversity and mutation. The evolution theory may also be referred to as the philosophizing science. This theory states that all phenomena are derived from natural causes and can be explained by scientific laws without reference to a plan or purpose.
Due to the development of ICT, adaptive learning, which takes into account individual learners’ needs, is changing. Learners’ learning styles are one of the most significant characteristics. They can be categorized according to a number of criteria which are based on cognitive and emotional components of personality. Their combination leads to the countless individual variants of real learning methods which – to a certain degree – can be influenced by the current e-learning resources. When the e-learning resources can react to the learners’ input characteristics or their learning results, they become adaptive e-learning systems (AES) or intelligent AES.
Genetic algorithms are a randomized search method which "breeds" effective solutions to problems through simulation of Darwinian Evolution. Large numbers of potential solutions are created at random. The solutions which show the most promise are then breed together to produce new solutions which receive most of their 'genetic stock' from the better solutions in the previous generation. This is similar to the "survival of the fittest" shown in biological systems, where the individuals which are best adapted to their environment breed more offspring, resulting in the better adapted genetic material carrying forward into future generations.
Various learning situations may dictate differing learning processes. The three that will be briefly highlighted in this paper are; learning by induction, through the use of decision rules or decision trees; learning by discovery; and learning by taking advice, explanation-based generalization. The concept of multi-strategy learning in order to handle more complex problems will also be examined.
Charles Darwin, the English naturalist and geologist is attributed and accredited for his theory of evolution. His theory of evolution is based on the premise that strong heritable traits help individuals to survive in adverse and inimical environments.
Without evolution, and the constant ever changing environment, the complexity of living organisms would not be as it is. Evolution is defined as a process that results in heritable changes in a population spread over many generations (8).Scientists believe in the theory of evolution. This belief is based on scientific evidence that corroborates the theory of evolution. In Figure 1 the pictures of the skulls depict the sequence of the evolution of Homo-sapiens. As the figure shows, man has evolved from our common ancestor that is shared by homo-sapiens. The change of diet of homo-sapiens over time has thought to contribute to the change in jaw structure and overall skull shape.