I'm Constantinos Daskalakis, also known as Costis Daskalakis. I'm a
professor of computer science at MIT and the Department of Electrical Engineering
and computer science and in the computer science and AI laboratory.
I love my work, it focuses on data interface between computer science
and game theory economics and there are several reasons why I'm
interested in this interface. One is a very practical reason and that's that a
lot of human economic activity is happening online on computation of
platforms so you need some handle to design these platforms in a way that
takes into account besides the computational issues also the strategic
an incentive issues so that's a very fact of reason why this interface is
important, especially when you know a lot of the economic activities up in your
line. But there's also a deeper philosophical reason why this is
important and that relates to the foundations of game theory in economics
which have to do with bounded rationality. When you make predictions
about what humans in a strategic scenario are going to be doing you
should also take into account that humans and are not infinitely rational
and in particular they have computational constraints in what
they're able to think about in a finite amount of time. So you really have to
inject into your game theoretic and economic approach to analyzing behavior
also the computational barriers that humans are going to be facing when
they're making decisions so that's yet another reason why this interface is
very interesting. Lastly there are very interesting mathematics and very
interesting computational questions that arise once you start thinking about our
interaction that motivates that interface even more.
Nash equilibria is a mathematical theory whose goal is to characterize
what happens when strategic individuals interact in a game or in a
very general notion of what a game is which is basically a strategic
interaction. Roughly speaking, a Nash equilibria is a strategy for every
individual participating in that interaction with the property
that given what the other players, what the other individuals are doing a
no-player unilaterally can improve his position by updating a strategy so
that's a Nash equilibria. It's a choice of strategy for every participant so that
everybody is happy at least they can all in the sense that they cannot unilaterally
improve their situation by changing their strategy. It could be that
you know where some global mood can make everybody happier but every individual
move cannot. So what my work with Goldberg and
Papadimitriou has shown is that when game is very complex when a strategic
situation becomes very complex it has a lot of moving parts
a lot of notes for the players to attune to update their strategies, then it may
be computationally really hard for the players to actually arrive at Nash
equilibrium. Which philosophically implies that if agents are computationally
bounded which they are they will actually not be able to discover a Nash
equilibrium in particular in this case the predictions of Nash equilibrium
should not be trusted as you know characterizing what really happens in
the situation of conflict.