Toward a Market Model for Bayesian Inference

We present a methodology for representing probabilistic relationships in a generalequilibrium economic model. Specifically, we define a precise mapping from a Bayesian network with binary nodes to a market price system where consumers and producers trade in uncertain propositions. We demonstrate the correspondence between the equilibrium prices of goods in this economy and the probabilities represented by the Bayesian network. A computational market model such as this may provide a useful framework for investigations of belief aggregation, distributed probabilistic inference, resource allocation under uncertainty, and other problems of decentralized uncertainty. 1 GENERAL MOTIVATIONS A principled market model for Bayesian inference would potentially address a variety of important and interesting problems of distributed uncertain reasoning. Although the particular contributions of our work to date do not deliver on these general problems, we present the big picture at the outset as und..