The WALRAS Algorithm: A Convergent Distributed Implementation of General Equilibrium Outcomes

  • Authors:
  • John Q. Cheng;Michael P. Wellman

  • Affiliations:
  • University of Michigan Ann Arbor, MI 48109 USA;University of Michigan Ann Arbor, MI 48109 USA

  • Venue:
  • Computational Economics
  • Year:
  • 1998

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Abstract

The WALRAS algorithm calculates competitive equilibria via a distributed tatonnement-like process, in which agentssubmit single-good demand functions to market-clearing auctions.The algorithm is asynchronous and decentralized with respect to both agents and markets, making it suitable for distributed implementation. We present a formal description of this algorithm, and prove that it converges under the standard assumption of gross substitutability. We relate our resultsto the literature on general equilibrium stability and some more recent work on decentralized algorithms. We present some experimental results as well, particularly for cases where the assumptions required to guarantee convergence do not hold.Finally, we consider some extensions and generalizations tothe WALRAS algorithm.