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ROBERT M. TOWNSEND: So let me just say that, shockingly, we have arrived at lecture 8, which means we're well more than halfway done with the lectures.
So today is continuing the theme of trying to bring computer science and economics onto the same page.
And the juxtaposition is everywhere today, so "Mechanism Design and Incentives" has to do with the way economists think about trust versus "Protocols and Notions of Trust" in computer science.
The longer title is "Private Information, Incentives to Report and Take Actions"-- as in mechanism design versus illustrative Byzantine Generals problem that utilizes a different notion of trust to emphasize the difference between economics and computer science in the way we think about algorithms,
which is not to say there isn't a middle ground. I'm trying to avoid a bipolar view, but that is the way the lectures are laid out.
So the outlined is information constrained allocations. And I'll do it through an example, Although the principles generalize.
And we'll think about implementing this without a planner in the jargon of economics, rather, using the tools of computer science.
So that helps mitigate the bipolar view of economics versus computer science. We will utilize the tools of computer science very heavily within the mechanism design problem.
And then we'll go on to talk about algorithms for validation and so on and readdress this difference by an illustrative paper of Steve Morris and Hyun Shin on the Byzantine generals problem.
So first half-- Information Constrained Allocations vis a vis this insurance example-- how to implement without a planner using the tools of computer science.
So to be specific, I will talk about an agrarian economy. But that said, we can think about this notation for the same model as applying much more generally to today's financial markets.