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This article explores combinatorial approximation algorithms for solving rational (nonlinear) convex programs in mathematical economics and game theory. It discusses the use of primal-dual paradigm and provides insights into finding equilibrium prices in various market models.
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Combinatorial Approximation Algorithms for Convex Programs?! Algorithmic Game Theoryand Internet Computing Vijay V. Vazirani Georgia Tech
Rational convex program • Always has a rational solution, using polynomially many bits, if all parameters are rational. • Some important problems in mathematical economics and game theory are captured by rational (nonlinear) convex programs.
A recent development • Combinatorial exact algorithms for these problems and hence for optimally solving their convex programs.
A central tenet • Prices are such that demand equals supply, i.e., equilibrium prices. • Easy if only one good
Irving Fisher, 1891 • Defined a fundamental market model
amount ofj Concave utility function (for good j) utility
Several buyers with different utility functions and moneys.Find equilibrium prices.
Combinatorial Algorithm for Linear Case of Fisher’s Model • Devanur, Papadimitriou, Saberi & V., 2002 Using primal-dual paradigm
Combinatorial Algorithm for Linear Case of Fisher’s Model • Devanur, Papadimitriou, Saberi & V., 2002 Using primal-dual paradigm Solves Eisenberg-Gale convex program
Eisenberg-Gale Program, 1959 prices pj
Why remarkable? • Equilibrium simultaneously optimizes for all agents. • How is this done via a single objective function?
Why seek combinatorial algorithms? • Structural insights • Have led to progress on related problems • Better understanding of solution concept • Useful in applications
Auction for Google’s TV ads N. Nisan et. al, 2009: • Used market equilibrium based approach. • Combinatorial algorithms for linear case provided “inspiration”.
Piecewise linear, concave utility Additively separable over goods amount ofj
Long-standing open problem • Complexity of finding an equilibrium for Fisher and Arrow-Debreu models under separable, plc utilities?
amount ofj Generalize EG program to piecewise-linear, concave utilities? utility/unit of j utility
Long-standing open problem • Complexity of finding an equilibrium for Fisher and Arrow-Debreu models under separable, plc utilities? • 2009: Both PPAD-complete (using combinatorial insights from [DPSV]) • Chen, Dai, Du, Teng • Chen, Teng • V., Yannakakis
Piecewise linear, concave utility Additively separable over goods amount ofj
What makes linear utilities easy? • Weak gross substitutability: Increasing price of one good cannot decrease demand of another. • Piecewise-linear, concave utilities do not satisfy this.
rate = utility/unit amount of j rate amount ofj Differentiate
rate = utility/unit amount of j rate amount ofj money spent on j
Spending constraint utility function rate = utility/unit amount of j rate $20 $40 $60 money spent onj
Theorem (V., 2002): Spending constraint utilities: 1). Satisfy weak gross substitutability 2). Polynomial time algorithm for computing equilibrium.
An unexpected fallout!! • Has applications to Google’s AdWords Market!
$20 $40 $60 Application to Adwords market rate = utility/click rate money spent on keywordj
Is there a convex program for this model? • “We believe the answer to this question should be ‘yes’. In our experience, non-trivial polynomial time algorithms for problems are rare and happen for a good reason – a deep mathematical structure intimately connected to the problem.”
Spending constraint market Fisher market with plc utilities EG convex program = Devanur’s program
Price discrimination markets • Business charges different prices from different customers for essentially same goods or services. • Goel & V., 2009: Perfect price discrimination market. Business charges each consumer what they are willing and able to pay.
Middleman buys all goods and sells to buyers, charging according to utility accrued. • Given p, there is a well defined rate for each buyer.
Middleman buys all goods and sells to buyers, charging according to utility accrued. • Given p, there is a well defined rate for each buyer. • Equilibrium is captured by a convex program • Efficient algorithm for equilibrium
Middleman buys all goods and sells to buyers, charging according to utility accrued. • Given p, there is a well defined rate for each buyer. • Equilibrium is captured by a convex program • Efficient algorithm for equilibrium • Market satisfies both welfare theorems!
Spending constraint market Price discrimination market (plc utilities) EG convex program = Devanur’s program