Abstract
We describe an Agent Mediated marketplace, with dynamically changing reputation ratings. In this marketplace, the seller reputations are updated in a collaborative fashion based on the performance of the user in the delegated tasks. We study the market with computer simulations of multiagent interactions, where sellers learn how to price their services dynamically. We first present some simple dynamic pricing methods and we investigate the different equilibria reached, based on the level of intelligence of the selling agents, the level of price-importance elasticity of the buying agents, and the level of unemployment in the marketplace. We then compare the equilibria reached with a theoretically equilibrium that we show to exist. Based on the results of this comparison we design a new dynamic pricing algorithm that we experimentally show to be almost optimal for reputation-brokered agent mediated marketplaces.
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