Answer key to radiometric dating assignment


20-Apr-2017 15:02

There are numerous natural phenomena for which evolution gives us a sound theoretical underpinning.

To name just one, the observed development of resistance - to insecticides in crop pests, to antibiotics in bacteria, to chemotherapy in cancer cells, and to anti-retroviral drugs in viruses such as HIV - is a straightforward consequence of the laws of mutation and selection, and understanding these principles has helped us to craft strategies for dealing with these harmful organisms.

These promising candidates are kept and allowed to reproduce.

Multiple copies are made of them, but the copies are not perfect; random changes are introduced during the copying process.

Methods of representation Before a genetic algorithm can be put to work on any problem, a method is needed to encode potential solutions to that problem in a form that a computer can process.

One common approach is to encode solutions as binary strings: sequences of 1's and 0's, where the digit at each position represents the value of some aspect of the solution.

answer key to radiometric dating assignment-61

Webcam roulette sexonline

However, purely by chance, a few may hold promise - they may show activity, even if only weak and imperfect activity, toward solving the problem.

The evolutionary postulate of common descent has aided the development of new medical drugs and techniques by giving researchers a good idea of which organisms they should experiment on to obtain results that are most likely to be relevant to humans.

Finally, the principle of selective breeding has been used to great effect by humans to create customized organisms unlike anything found in nature for their own benefit.

Moreover, the solutions they come up with are often more efficient, more elegant, or more complex than anything comparable a human engineer would produce.

In some cases, genetic algorithms have come up with solutions that baffle the programmers who wrote the algorithms in the first place!

As astonishing and counterintuitive as it may seem to some, genetic algorithms have proven to be an enormously powerful and successful problem-solving strategy, dramatically demonstrating the power of evolutionary principles.