Introduction to Computational Game Theory

Another module in the first semester of my final year was Game Theory. To the uninitiated, this may sound like some kind of Computer Games Technologies module, not so much.

‘Games’ refer to mathematical games – the idea that decision-making can be represented mathematically in many situations. This was only an introductory course, so remained relatively simple, but was fascinating none the less. Discovering that even theoretically, as long as everyone is telling the truth, truthfulness remains the dominant (optimal) strategy, was particularly poignant.

We were taught about finding Nash Equilibria (the combination of choices under which no player wishes that they had made a different choice), about auctions of different types, and about the strategies used by search engines to auction off page positions for particular queries. We also covered potential games  as well as matching markets- finding the optimal result for all sellers and buyers in a market (those with higher valuations of a product are more likely to get it, and others will get a different product) – and finding market clearing prices – the prices at which each product would be preferred (or is indifferent for) a buyer.

Although I’m unsure whether selecting this module was the most useful for my desired future career in software development or web development, I was fascinated by the topic and priveleged to take advantage of the opportunity to be (wow, if we had a simple word like aprovechar eh?) taught by Professor Paul Spirakis, who had casually proved some unproved theorem or something over the summer before returning to teach us.

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