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General equilibrium theory has been proposed for resource allocation in computational markets. The basic procedure is that agents submit bids and that a resource (re)allocation is performed when a set of prices (one for each commodity) is found such that supply meets demand for each commodity. For successful implementation of large markets based on general equilibrium theory, efficient algorithms for finding the equilibrium are required.

We discuss some drawbacks of current algorithms for large scale equilibrium markets and present a novel distributed algorithm, CoTree, which deals with the most important problems. CoTree is communication sparse, fast in adapting to preference changes of a few agents, have minimal requirements on local data, and is easy to implement.