Nature creates and operates it’s systems efficiently. Natural processes and nature’s “problem-solving methods” emanate originality, precision, and incredible utilisation of resources. It is no wonder why we always return to them when everything else fails or when we are in need of an excellent solution. The natural world is the most adaptable complex system ever known to humans. Evolution provides us with countless examples of systems performing various types of computations. We harnessed some of these ideas and created artificial systems comparable with natural ones, like optimisation algorithms inspired by ant colonies (ACO). This type of probabilistic models is useful for finding optimal solutions for situations encountered in operations management, like the shortest path problem, combinatorics problems in resource allocation, multi-objective optimisation problems. For example, maritime transport systems rely on ACO for route planning and collision avoidance [1]. Also, ACO generated many efficient designs for routing in wireless sensors networks [2]. Nature is an excellent source of inspiration for designing systems that surpass human capabilities and display unexpected efficiency levels.
The natural world has always designed intelligent systems. Chemical networks, cells, our brain, or our societies are examples of adaptive and autonomous systems. Everywhere you look, the natural world bursts with examples of complex adaptive systems. However, nature has a significant advantage on its side: time. The majority of these systems are the result of years and years of evolution. Years during which they went from one configuration to the next until they found the best way to solve the task. Fair enough, sometimes constraints prevented a natural system from finding the best solution. Those situations had catastrophic consequences such as the extinction of a species or the loss of a large number of members of a population. Technology does not have the luxury of perfecting a solution over millions of years nor can we afford catastrophes. With all their differences, nature and technology should not be excluding each other. We should pay close attention to the natural world. Start by finding out if a biological system has not already solved the problem. If it has, then there is no point in reinventing the wheel, extract the fundamental principles and methods and transfer them to the problem we are trying to solve. Nature is a source of inspiration, while technology is the engine for creation.
Developments in artificial intelligence relate to biological and the natural world. We developed many algorithms and systems inspired by systems found in nature. Examples are evolutionary algorithms, artificial neural networks computational immunity systems, bio-robotics, swarm intelligence or optimisation algorithms based on colonies, hives, or flocks. These ideas transformed how we develop new technologies and solve problems. Bio-inspired solutions benefit from the fact that nature has already refined a lot of the steps to make them as efficient as possible. Thus, we will develop disruptive technologies by combining engineering and natures fine-tuned solutions.