The natural world helps design intelligent systems

Living organisms are, in essence, complex systems which process information using a combination of hardware and software. Over time, people figured this out and started to use natural systems as inspiration for efficient solutions.

According to Franco Lodato, VP of Desing, Exploration, and Development at Herman Miller, nature is a “database” that helps you understand design opportunitiesIf we listen to what nature is telling to us, we can take better decisions, build more sustainable buildings, create systems that function where and when we need them to, all in one, assign nature solution to human problems. Nature is an ecosystem made from living organisms like us humans.

Artificial intelligence (AI) seeks to design and build computational systems that can reason, sense, and make decisions in complex environments and under much uncertainty. The connection between artificial intelligence and nature helps to create advanced technologies. Understanding the processes behind any form of intelligence occurring in the animated world will reshape business and industrial processes.

AI is closely related to biology, neuroscience, or cognitive science. Scientists and practitioners borrowed many ideas from the natural world about computation. AI algorithms and in some instance entire fields derive from biological systems. For example, neural networks use elements from the architecture of the brain. Moreover, we have optimisation algorithms inspired by natural evolution, ant colonies, or immune systems. Thus, AI and the natural world share many similarities.

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.


[1] Lazarowskaa, A 2014, ‘Ant Colony Optimization based navigational decision support system’, Procedia Computer Science, vol. 35, pp. 1013-1022, viewed 04 July 2018, available at:

[2] Okdem, S & Karaboga, D, 2009, ‘Routing in Wireless Sensor Networks Using Ant Colony Optimization (ACO) Router Chip’, Sensors, vol. 9, pp. 909 – 921

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