What does Charles Darwin has to do with A.I.?, you might ask.
The answer, everything.
Through his research and writings, he completely changed the way we see lifeforms. He explained how natural selection makes evolution possible.
Through the genetic algorithm in artificial intelligence, scientists have been able to adapt the concept of natural selection to further machine learning.
Let’s explore how this works.
An Understanding Of The Genetic Algorithm In Artificial Intelligence
To lay the groundwork for a discussion about programming, let’s first review a more familiar concept to most of us — biology.
Darwin studied animals of the same species who’d been “stranded” on the various Galapogos islands. These islands are home to some of harshest landscapes on the planet.
He found that the animals had adapted genetically over time, based on the habitat of their island
Through the process of natural selection, animals with a genetic makeup that gave them a better shot at surviving survived and reproduced.
Those who had genes that made them less able to survive in their climate died.
If a genetic mutation made it easier to survive, then others with the same mutation would breed. The mutation would become a part of that species’s genetic code.
Natural Selection in the Genetic Algorithm in Artificial Intelligence
The concept of natural selection isn’t limited to organic creatures like humans. A.I. can also adapt in this way through machine learning.
They can begin with a standard “genetic makeup” and over time they can adapt to their surroundings.
They can learn how best to respond to challenges and solve problems.
How Does Natural Selection Take Place in Machine Learning?
It all starts with a large population of what we’ll call “chromosomes”. You probably remember those from high school biology class.
You start with a large number of these chromosomes. Each one is pre-programmed to be the solution to a problem.
These chromosomes then get to work solving problems. Each solution is provided with a “fitness score” that indicates how well that chromosome actually solved the problem.
Next, in line with the natural selection process in organisms, those chromosomes with the highest fitness levels do the A.I. version of mating.
Their codes are combined. Only a portion of each code becoming part of their offspring.
So what happens to the chromosomes who couldn’t find effective ways to solve a problem? Just like natural selection, they die out. They’re not chosen for the reproduction process and therefore cease to exist.
When Natural Selection Becomes Evolution
Over time, this genetic algorithm in artificial intelligence completes this process repeatedly.
Depending on the level of A.I., this may be just to find the ultimate answer to a single question. Or within a complex A.I. this process may happen for seemingly infinite scenarios and solutions.
As the genetic algorithm in artificial intelligence continues to work, the A.I. gets “smarter”. It’s better able to solve problems and respond in the appropriate way.
This could even include the ability to converse with a human in a seemingly natural way. In many cases people don’t know they’re speaking with A.I.
Real World Application
This technology can be applied to improve patient care by aiding doctors in the decision making process. By learning the best ways treat various patients they can meet unique patient needs.
It can be used in marketing to engage potential customers.
It can be used in business to automate monotonous processes that once required a person. It can thus significantly increase productivity.
What could you do with this kind of machine learning? It’s time to find out.
It’s time to Meet Sally, your personal A.I. assistant. Contact us to learn more about how we can help you with this A.I. technology.