The Complexity Blog

Editor´s Note: At Innaxis we are starting a new series that involves contributions from individuals that work at Innaxis. Below is our first contribution from Alberto.

It’s nice to learn new things every once in a while. I’m not a mathematician but I am definitely intrigued by the way some things work and how they can be studied. Recently I have been investigating lately about agent-based modeling.

Agent-based modeling is a relatively new science that is being used to analyse systems that are composed of many elements. In the Cassiopeia project, these elements are the airplanes, airlines, airports, air navigation service providers, and the passengers.

The nice thing about the agent-based models (ABMs) is that we can assign some decision making attributes to each element and see what happens when we run the program. Another important aspect of ABMs is that we can design the strategy of some elements, since sometimes what’s best for a single element is not the best for the team.

To put this in context, we can look at Russell Crowe’s character ¨John Nash¨ in the movie “A Beautiful Mind.¨ In one scene, his character explains that a group strategy does not necessarily require each member to achieve best possible outcome individually (which was in their case, for no one to approach the blonde woman). Often times when studying aircraft, we need to approach problems in a similar way- figuring out the group strategy that suits everyone in a collective sense. An example of this would be the distribution of delay amongst all the aircraft rather than having a few aircraft support the entire delay. This becomes a bit challenging as it would be much more easier and convenient to have solutions be based on key individual factors (one man approaches the woman; few aircraft bear the burden of delay), however we learn and demonstrate in the Casseiopeia project that agent-based modeling is actually the best way to resolve situations. In the end more is benefited from a involving multiple elements rather than just a few.