Ever since ancient times, mankind have adapted numerous ways to do their computation.

Everything started out when ancient sheep keepers wanted to ensure that at the end of a long

workday, no sheep were lost. And they’ve done that by counting the sheep using stones. And

arithmetic was born. As the human race developed, so did its need of computation. And the

formulas they used in order to express the world around them got more and more complicated.

Until the point where they started building special purpose machines to solve these

computational problems around them. And the abstract concept these machines were built on is

what’s known as the “Computational Model” or “Model of Computation”.

Early models of computation include Babbage’s “Difference Engine”. Which was a mechanical

device capable of basic arithmetic operations, such as addition and subtraction. Although addition

is a relatively easy task for the human mind compared to, say, solving third-order differential

equations, but the difference engine was very, very fast. Simply because the position of a node in

the Difference Engine, unlike a thought cannot be misinterpreted. After that, the second

generation of the Difference Engine came about. And this one was capable of solving ballistics

equations. Now, we’re going somewhere.

And of course, how can we forget about the famous Enigma code! and the genius who cracked

it, Alan Turing. What really happened is that Turing discovered the flaw in the Enigma

encryption scheme. But the heavy duty work was left for Bombe, a powerful computer that

Turing built in order to cope with the enormous computations involved in cracking the code.

In the present, different discoveries led to different models of computation. Such as the Turing

machine, cellular automaton and others. Although all of them have been proven to be equivalent,

some are better at certain tasks than others. furthermore, some gave birth to entirely new scientific

concepts. This does beg the question; why do we use so many models of computation? What

advances did this diversity lead to? And most of all, is there some superior model that can be used

instead of all the others combined?

In this seminar, we shall introduce some of the most famous models of computation. Later, we

will look at different comparisons between these models, to show the strengths and weaknesses

of each model. Hopefully, we will be able to know when to use each model, and therefore choose

the optimal model for several scientific fields.

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