A Study On Genetic Programming

Figure 10 shows the results between the hybridg algorithm compared to other algorithms with various mathematical functions as presented by privous sessions. It is cleard to see that the hybride algorithm performed better than other techniques. Surrprisingly, the Ackley function performed closely to the hybride algorithm. Figure 11 - 14 shows that PSO reached the optimal result very quickly because this algorithm works as a local search which makes a narrow space for the search of a solution, rather than other algorithms which work as a global search

Andrew Niccol’s, Gattaca, shines light on our possibly not so bright future. The film is based off genetic engineering and its effects on society. When a couple wants a child, they head to the clinic with their list of preferences. The fetus is then altered to meet these preferences. Society is now classified into groups: the “valids” and “invalids” – basically a caste system. The movie focuses in on an “invalid” named Vincent Freeman, and how his genetics hold him back from achieving his dreams. Vincent dreams of space travel, something someone of his caste would normally never experience. Although with perseverance and the help of loyal friends Vincent is able to fight for a chance of reaching his dreams.

It’s been seen in movies like Gattaca, and now reality is catching up to fictional genetic engineering. Genetic engineering is defined as the deliberate modification of an organism’s characteristics by manipulating genetic material. Rapid progression in this field has already taken place; today, over 40% of the world’s food is genetically modified and this science has begun to allow parents to select the traits they want in their children. As of right now, genetic engineering is a fresh concept not completely accepted or understood, but by 2041, it will as common practice as smartphones are commonplace because of its contribution to the quality of life.

Does changing a babies genetic coding help or harm them? Since 1975 it has been possible to choose the gender of your baby before even becoming pregnant with a child. Now you can take genes from an unborn child and change their genetic coding to prevent genetic diseases. People should not be allowed to genetically engineer their baby, even though it has the potential to prevent disease, it is potentially harmful to the baby and not 100% effective.

There are 20 canonical amino acids that are encoded by the genetic code of nearly all known organisms. There are only very few exceptions. In order to add novel building blocks to this existing repertoire, unique aminoacyl-tRNA synthetase and tRNA pairs are required, in addition to the specific amino acid codon as well as a source of the amino acid. In terms of biological evolution, it is known that our ensemble of 20 amino acids has remained unchanged over a period of 3 billion years. This is demonstrated by the fact that all living organisms have adopted it.

On a State Judo competition a 9-year-old girl was laying in the floor screaming, after her opponent just felt on top of her right arm. The EMT suggested the girl couch to take her to the emergency room, but her couch asked her if she was able to wait until they returned to their hometown. When she arrived in her hometown, her parents go took her to the emergency room. Getting in the hospital with her mother find out that she had a fracture.

A child's life should not be taken on as a blueprint. The modification of genes in the child contributes to the risk of losing individuality and natural differences. Like fingerprints, everyone has their own unique structure. So in effect of electing specific traits, the unique factor of the human being will be challenged. Scientists are developing tests having to do with eye color, behavior, nutritional background associated with disease, and athleticism. These tests are challenging the “one in a million” traits and behaviors of a natural birth, which leads to a damaging effect on natural differences. In the article Opposing Views, it was stated by scientist that there is an “increasing number of humans with similar traits, and a number of

The movie’s portrayal of scientists makes human manners towards the Na’vi look bad because some of the humans did not care about the Na’vi. The military and the big corporation would kill the whole native species before giving up the supply of unobtanium. They would kill their own men who betrayed them to get the unobtanium. The scientists were able to genetically engineer modified human DNA with Na’vi alien genetic material to create avatars, which through psionics humans could “mind link” with their avatars. In today’s world, genetic engineering is a touchy subject. In fact, we are having a whole Nobel conference over it in 2017, to debate if it is ethically moral to genetically modify humans. Gattaca was an entire movie based on genetic engineering. Genetically engineering a species can have many bad points like one specific disease could wipe out the whole human race natural selection would not be on our side. There are many good scientific points supporting genetic engineering too. You can get rid of some diseases such as down

\emph{Genetic Programming} is inspired by Charles Darwin's \cite{darwin2009} evolution theory and the principle of natural selection. Organisms that are most fit for their natural habitat have the highest probability of reproducing and, therefore, preserving their genetic material for subsequent generations. As the natural habitat changes with time, the definition of fitness changes too. Also, the sophistication of organisms has changed from unicellular organisms to Homininae, Australopithecines to finally Humans. It is important to note that evolution is not a random process. It does, however, have random components, for example, it is not precisely determined which individuals mate, yet chances are heavily influenced by their ability to adapt

The genetic code can be defined as a series of rules that determine how genetic material is translated into proteins. Specifically, it refers to the correspon- dence between a particular amino acid and a group of codons [8]. The first amino acid-codon association to be uncovered was phenylalanine and the codon con- sisting of three uracil ribonucleotides [9]. A monu- mental achievement of modern science, the unravel- ing of this code has allowed researchers to synthesize proteins using transcriptional machinery. Human in- sulin, for example, is synthesized for pharmaceutical use by applying this knowledge [13]. Questions on the origins of this newly-deciphered code, however, remained unanswered.

TH Morgan concluded that chromosome play an important part in heredity and the passing on genetic traits

–Evolutionary reasonable strategy –Helpful but can lead to severe errors –Can result in biases –People are unaware of using heuristics most of the time –Why important to understand

Genetic engineering is using molecular biology methods to modify the genetic information of an organism. Its aims include learning about the biology of an organism and generating new or improved commercial products. Plant biotechnology is manipulating plants specifically to improve agricultural needs. GMOs or genetically modified organisms are organisms modified by genetic engineering to express desirable traits. DNA fragments containing said desirable traits and a means of introducing the DNA to the host plants is required for genetic engineering. Some common methods of introducing DNA fragments to plants include the use of viruses, chemicals, some means of physical insertion, or the use of agrobacterium.

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This project comprises the application of genetic algorithm in the process of sound evolution using Darwinian Theory of ‘survival of fittest’ whereby its emergent behaviour is employed to produce sound which evolves towards better solution by adapting to the environment over the numerous generations using its simple operations of selection, crossover and mutation. In the context of sound evolution, genetic algorithm has been used to evolve musical notes where the process of fitness function is employed to measure the fitness of candidate solution that takes into consideration the numbers of criteria need to be exists in candidate solution to make individuals rhythmic in nature. The role of genetic algorithm in the process of sound evolution is considered to be vital as far as evolutionary computation is concerned which best suits the application domain in this project. To produce rhythmic sound, numbers of criteria are considered into the fitness function since it does shape the population significantly followed by the rating of individuals based on existence of those criteria into population expected from fitness function. The overall idea of this project and hence the genetic algorithm in sound evolution is to converge the population towards rhythmic sound since the criteria are expected from fitness function that leads the function of selection towards the consideration of those individuals who are most fit followed by the rejection of least ones.