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Algorithmic Game Theory and Internet Computing Amin Saberi Stanford University Computation of Competitive Equilibria
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Outline History Economic theory and equilibria (existence, dynamics, stability) An algorithmic approach: computation, polynomial time computability
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A bit history Rabbi Samuel ben Meir (12th century, France): 2nd century text: “You shall have inspectors of weights and measures but not inspectors of prices.” Commentary (Aumann): If one seller charges too high a price, then another will undercut him. Adam Smith (1776): Capital flows from low-profit to high- profit industries (demand function implicit?)
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The beginning of analytical work Standard analysis demand functions: Cournot (1838) supply functions: Jenkin (1870) excess demand: Hicks (1939). Dynamics in 1870’s: Is out-of-equilibrium behavior modeled by demand and supply?
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Walras, Fisher, Pareto, Hicks Walras [1871, 1874]: first formulator of competitive general equilibrium theory. Recognized need for stability (how to get into equilibrium) His name: tatonnements (gropings).
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Walras, Fisher, Pareto, Hicks Walras [1871, 1874]: first formulator of competitive general equilibrium theory. Recognized need for stability (how to get into equilibrium) His name: tatonnements (gropings). Fisher (1891): tried to compute the equilibrium prices
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First computational approach! Fisher (1891): Hydraulic apparatus for calculating equilibrium
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Walras, Fisher, Pareto, Hicks Walras [1871, 1874]: tatonnements Pareto (1904): Pointed out that even a simple economy requires a large set of equations to define equilibrium. Argued that market was an effective way to solve large systems of equations, better than an “ordinateur” (his word in the French translation). I believe this is the word now used to translate, “computer.”
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Walras, Fisher, Pareto, Hicks Walras [1871, 1874]: tatonnements Fisher (1894), Pareto (1904): Markets and computation Hicks (1939): convergence and “Hicksian” condition on the Jacobian of the excess demand functions (the determinants of the minors be positive if of even order and negative if of odd order)
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Samuelson and successors Samuelson [1944]: Hicksian conditions neither necessary nor sufficient for stability. Metzler [1945]: if off-diagonal elements of Jacobian are non-negative (commodities are gross substitutes), then Hicksian conditions are sufficient. Arrow [1974]: Hicksian conditions were actually equivalent to the statement that the real roots of the Jacobian are negative.
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Arrow, Debreu and… Arrow-Hurwicz et. al. papers [1977]: Sufficient conditions for stability of Samuelson-Lange system Gross substitution implies that Euclidean norm decreases Will talk about these dynamics in details in the next lecture Arrow-Debreu: existence of equilibrium prices (will show a variation of Debreu’s proof)
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End of the program? Scarf’s example, Saari-Simon Theorem: For any dynamic system depending on first-order information (z) only, there is a set of excess demand functions for which stability fails. Uzawa: Existence of general equilibrium is equivalent to fixed-point theorem (will show in this lecture) Linear complementarity Programs (LCP) and algorithms: Scarf, Eaves, Cottle…(later in the quarter)
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Outline History Economic theory and equilibria (existence, dynamics, stability) An algorithmic approach: computation, polynomial time computability
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New applications: Internet, Sponsored search, combinatorial auctions Computation as a lense! First papers: Megiddo 80’s, DPS 01 prices and ND communication complexity Lots of new algorithm: convex programs combinatorial algorithms Last 10 years
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n buyers, with specified money m divisible goods (unit amount) Buyers have CES utility functions: Contains several interesting special cases: = 1 linear = 0 Cobb-Douglas = - 1 Leontief (rate allocation in a network) A CES Market
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n buyers, with specified money m divisible goods (unit amount) Buyers have CES utility functions: Contains several interesting special cases: = 1 linear = 0 Cobb-Douglas = - 1 Leontief (rate allocation in a network) A CES Market
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n buyers, with specified money m i m divisible goods (unit amount) Buyers have CES utility functions: Find prices such that buyers spend all their money Market clears Market Equilibrium
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Buyers’ optimization program: Global Constraint: Market Equilibrium
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The space of feasible allocations is: How do you aggregate the utility functions U 1, U 2, … U n ? Eisenberg-Gale’s convex program
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The space of feasible allocations is: How do you aggregate the utility functions U 1, U 2, … U n ? First observation: Adding them up is not the answer! Eisenberg-Gale’s convex program
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Buyer i should not gain (or loose) by Doubling all u ij s By splitting himself into two buyers with half of the money Eisenberg-Gale’s convex program
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Buyer i should not gain (or loose) by Doubling all u ij s By splitting himself into two buyers with half of the money Eisenberg-Gale’s solution: Eisenberg-Gale’s convex program
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Optimum dual: Equilibrium prices (also unique) Gives a poly-time algorithm for computing the equilibrium Eisenberg-Gale’s convex program
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Optimum dual: Equilibrium prices (also unique) Gives a poly-time algorithm for computing the equilibrium Market is “proportionally” fair for every other allocation achieving Eisenberg-Gale’s convex program
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Optimum dual: Equilibrium prices (also unique) Gives a poly-time algorithm for computing the equilibrium The program works for all homogenous utility functions, generalized to homothetic KVY 03 (homothetic: U(f(y)) U is homogeneous of degree one and f is a monotone) Eisenberg-Gale’s convex program
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Application: Congestion Control x1x1 x2x2 x3x3
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Congestion Control $ $ $ Find the right prices in a Leontief market p 1 = p 2 = 3/2
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Primal-dual scheme primal: packet rates at sources dual: congestion measures (shadow prices) A market equilibrium in a distributed setting! Kelly, Low, Doyle, Tan, …. Congestion Control
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Exchange Economy Agents buy and sell at the same time:
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Exchange Economy Agents buy and sell at the same time: - 1 -1 0 1 At least as hard as solving Nash Equilibria (CVSY 05) Polynomial-time algorithms known (DPSV 02, J 03, CMK 03, GKV 04,... OPEN!!
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Nash = Leontief Use LCP as an intermediate step: Finding the solution of LCP for H > 0 Nash equilibria for a symmetric game H x is equilibrium if:
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Nash = Leontief Finding the solution of LCP for H > 0 Leontief: H the rate matrix; agent i owns good i x is at equilibrium if:
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Open Questions Exchange economies with - 1 < < -1 Markets with indivisible goods Price equilibria; proportional fair allocation Core of a Game: LP-based algorithm for transferable payoff Still open for NTU games
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Nash = Leontief In Leontief markets, agents consume goods in fixed proportions: Let H > 0 be the utility matrix. Assume agent i owns good i x is an equilibrium if
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