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authorPaul <Paul@Pauls-MacBook-Air.local>2014-12-15 18:59:46 -0500
committerPaul <Paul@Pauls-MacBook-Air.local>2014-12-15 18:59:46 -0500
commitdd13f5b0d7afd397b5207a4b5994c8e61ed97163 (patch)
tree2180f976830c0ee8c0cef33d4e435c2851f252c2 /project2
parent342435c8e708ebcb0ec442960f1ebd6a64c9711a (diff)
downloadecon2099-dd13f5b0d7afd397b5207a4b5994c8e61ed97163.tar.gz
Added stuff
Diffstat (limited to 'project2')
-rw-r--r--project2/main.tex23
1 files changed, 16 insertions, 7 deletions
diff --git a/project2/main.tex b/project2/main.tex
index dc863df..96a1d6b 100644
--- a/project2/main.tex
+++ b/project2/main.tex
@@ -22,6 +22,13 @@
\setlength{\itemsep}{-1ex} \setlength{\parsep}{0pt}}%
{\end{description}}
+\newcommand\blfootnote[1]{%
+ \begingroup
+ \renewcommand\thefootnote{}\footnote{#1}%
+ \addtocounter{footnote}{-1}%
+ \endgroup
+}
+
\DeclareMathOperator*{\E}{\mathbb{E}}
\let\Pr\relax
\DeclareMathOperator*{\Pr}{\mathbb{P}}
@@ -37,14 +44,15 @@
\author{Thibaut Horel \and Paul Tylkin}
\title{Economics 2099 Project}
-
\begin{document}
\maketitle
+
+
\section{Introduction}
-We consider the problem of selling $m$ heterogeneous items to a single agent
+\blfootnote{We are deeply grateful to Jason Hartline who provided the original idea for this project.}We consider the problem of selling $m$ heterogeneous items to a single agent
with additive utility. The type $t$ of the agent is drawn from a distribution
$F$ over $\R_+^m$. For an allocation $x = (x_1,\ldots,x_m)$ where $x_i$,
$i\in[m]$, denotes the probability of being allocated item $i$ and payment $p$,
@@ -99,9 +107,10 @@ $\hat{x}$.
To provide some more intuition about this, we assume that the buyer is charged a price $p_0$ to participate in the mechanism,
and then is offered a menu of goods with prices $p_1,...,p_m$. The buyer's utility over the goods is additive, as above. However, there is an ex-ante constraint of being allocated a given good $i$, given by $\hat{x}_i$. For each good, if the buyer is allocated the good, which he is with probability $x_i \leq \hat{x}_i$, then he pays $p_i$; otherwise, he pays nothing. This is essentially the concept of a two-part tariff, as discussed in \cite{armstrong}.
+
-Let us denote by $R(\hat{x})$ the revenue obtained by the optimal mechanism
-solution to Problem~\ref{eq:opt} with ex-ante allocation constraint
+We use the notation from \cite{alaei} where $R(\hat{x})$ denotes the revenue obtained by the optimal mechanism
+solution to Problem~\ref{eq:opt} with ex-ante allocation constraint $\hat{x}$.
\eqref{eq:ea}.
\paragraph{Problem.} \emph{Given an ex-ante allocation constraint $\hat{x}$, is
@@ -123,12 +132,12 @@ answer to our problem:
\item when $\hat{x} = (1,\ldots,1)$, \eqref{eq:ea} does not further
constrain Problem~\ref{eq:opt}, i.e. the constraint is trivially satisfied.
In this case, as discussed above, the
- mechanism described in \cite{babaioff} provides a 6-approximation.
- \item when $\hat{x} = (\frac{1}{m},\ldots,\frac{1}{m})$, by summing the
+ mechanism described in \cite{babaioff} provides a 6-approximation to $R((1,...,1))$.
+ \item when $\hat{x} = \left(\frac{1}{m},\ldots,\frac{1}{m}\right)$, by summing the
constraint \eqref{eq:ea} for all $i\in[m]$, we see that the ex-ante
allocation constraint implies that in expectation, no more than
one-item is sold to the agent. This is exactly the unit-demand case for
- which TODO:cite provides a 2 approximation.
+ which TODO:cite provides a 2 approximation to $R\left( \left(\frac{1}{m},\ldots,\frac{1}{m}\right)\right)$.
\end{itemize}
\section{Related Work}