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Artificial life & Complex systems

Bio-phenomena approaches to solve complex problems 

The last 20 years has seen a rise in technology use and an increase in interconnectedness and interdependence in all aspects of our lives, from our social networks to supply chains and economies. Traditional linear “cause and effect” thinking, that worked in a simpler world, no longer works in today’s dynamic, unpredictable and multi-dimensional world. New approaches, new thinking and new techniques are needed to learn, grow and adapt to solve today's wicked problems.

“Complex” systems are characterised by heterogeneous components, or agents, interacting with each other, leading to emergent behaviour. In a complex system, the same starting conditions can produce different outcomes, depending on the interactions of the elements in the system.

 

“The whole is greater than the sum of its parts”

 

Using agent based modelling, simulations and complexity science, we seek to better understand the complex problems that challenge all businesses today.

 

"Complex systems—business process workflows, for example, or the way customers move through a store—are hard to understand, much less fix, if you can’t first see them.” - Harvard Business Review

 

We use algorithms inspired by natural bio-phenomena, such as the flocking of birds, schooling of fish, ants foraging, the crossover and mutation of DNA, fireflies synchronising their lights, and others, to solve increasingly complex problems for which traditional methods are not effective.

 

“Life finds a way” - Dr. Ian Malcolm

 

From artistic explorations of Langton's Ants, to genetic algorithms solving trail following problems and flocking algorithms combined with cellular automata to cluster and understand patterns in survey comments; Flink Labs is actively engaged in applied research and live client implementations of Artificial Life inspired projects.

Flink Labs is a member of the International Society for Artificial Life.