Nature is dynamic and evolving and therefore, it serves as a great source of inspiration for the algorithms of Artificial Intelligence. The evolution of AI marks many moments when they find their inspiration from nature for the development of a new generation of intelligence on the planet. Mother Nature, and all that it entails, has its existence firmly ingrained in the systems of Artificial Intelligence and will continue to be an integral part of AI for a long run.
Some of the most appreciated AI algorithms that were inspired by nature are covered below:
1- Artificial neural networks
It is inspired by one of the most powerful weapons on the planet – the human brain and its cognitive functions (neurons). Neural networks are an important element of machine learning and they try to mimic the functioning of the human brain with the use of neurons, axons, and dendrites by passing information through a system and generating a worthwhile result. Our brain is capable of making instant decisions and therefore it works efficiently within microseconds and provides the right reaction to a stimulus. Artificial neural networks replicate the functioning of the human brain and its elements to solve problems within a very short period of time with accuracy and are very helpful in image recognition, pattern recognition, and classification of data in meaningful categories.
2- Genetic algorithms
Inspired by human evolution and the concept of natural selection and genetics, Genetic algorithms are utilized in solving optimization problems. Survival of the fittest or natural selection simply means that those species in nature that can adapt to the changing environmental conditions have the best chances of surviving and reproducing the next generation. Genetic algorithms are mostly used in the process of data mining, robotics, and process optimisation.
3- Swarm intelligence
We all have witnessed ants carrying out unbelievable functions. If you observe closely, you will notice that each ant works as a unit and collectively, they work as a force that carries out complex roles and responsibilities. Each ant makes decisions on the basis of certain receptions and thus, plays a key role in the complete process. Taking inspiration from these ants, swarm intelligence was developed to solve complex problems and optimization tasks. Swarm intelligence is generally incorporated in robotics, IoT, and AI video gaming.
4- Reinforcement learning
Animals can be trained to do or not do a certain thing by their trainers with the help of a reward system. Just like that reinforcement learning can be used to train machine learning models to perform a particular task or take a particular decision by conditioning. To make it effective, the programmer makes use of a reward system and each time a decision is made by the machine, subsequent reward or penalty is given to it. With the final aim to make the most reward, the machine makes use of trial and error methods to complete a task. Thus with every decision, and every task performed, the memory is stored and is used while making the next decisions. It is very common in video games and in controlling autonomous vehicles.
5- Artificial immune systems
Humans have a biological immune system that helps our body to protect itself from outside substances like pathogens and bacteria. Our body can differentiate between its own cells and outside cells and thus acts on the outside cells and kills them with the help of antibodies. Just like that, machines are trained to identify cyber-attacks and protect themselves from such attacks by monitoring intrusion.
Nature is full of inspiration and complex mechanisms that help the sustainability of life on the planet. AI is taking a step forward to understand these processes and utilise them for processing new intelligence for a better future.