The hardest problem

As an engineer, I spend the most of my time trying to find inventive solutions of tough and tricky problems. So much so that I have got into the habit of analyzing every circumstance concerning me with some techniques that are incredibly useful when it comes to approach an academic problem.

Computer Science stands over the basis of formalizing Human’s ideas. Once you have transformed your problem in a set of variables –the elements you think your problem depends of– and constraints over these variables –how these elements are related to each other, and what properties they must satisfy-, one can start discussing about its nature and the ways to solve it. When one have been dealing with these sort of problems over the years, innately acquire a third eye, a natural intuition that makes you shrewd identifying the key aspects of them.

In certain areas of daily life, such as planning or deciding what is the best way to perform one action or a sequence of them, having this hability might save you a great deal of effort. The class of matters that are approachable from this perspective tend to share a common goal: maximize benefits while minimizing cost, used resources or effort. This structure permits, given two different potential solutions, decide whether the first one is better than the other one or viceversa, always in terms of optimality.

Whereas the previously mentioned scheme targets the questions How do I… ? ,  It is possible to… ?, there are other kind of enquiries that gets too hard to compute, or decide. The dificulty arises when the decision made involves many agents, or has unpredictable implications, and it is not always possible to obtain a verifiable best option. And that without including the cases in which it is impossible taking into account all the parts that, to a greater or lesser extent, would be affected.

Questions of the form Should I… ? are a good example. The more deeper the question, the harder is the decision. It is incredible how a problem with that reduced set of possible solutions gets as difficult. There is not an optimal solution to this. We cannot even, given an answer, check whether it is correct or not.

This indeterminism forces us to guess. And guessing is not a reliable source of knowledge, like it is of inaccuracy. We are condemned to be ignorants. Ignorants because there are problems we are not capable to solve. You may think that is not as grave, since the solution does not even exist, but it means loosing the game before playing it, and it is terribly disheartening.

On the other hand, if everything was deterministic, life would certainly diminish its excitement. The complexity of everything we can think of is, in a certain way, what makes it interesting to us. We have the –kind of– luck of being curious about the universe that embraces everything we know and we do not, and it is that curiosity that encourage us as individuals as well as as spices to grow up and be better day after day. Our imperfection makes us overambitious in a measure we cannot be aware of. But this let us dream, let us believe.


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