Partially observable stochastic game-based multi-agent prediction markets

Authors:
Janyl Jumadinova;Prithviraj Dasgupta
Affiliations:
University of Nebraska at Omaha, Omaha, NE;University of Nebraska at Omaha, Omaha, NE
Venue:
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Year:
2011

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Abstract

We present a novel representation of the prediction market using a partially observable stochastic game with information (POSGI), that can be used by each trading agent to precisely calculate the state of the market. We then propose that a correlated equilibrium (CE) strategy can be used by the agents to dynamically calculate the prices at which they should trade securities in the prediction market. Simulation results comparing the CE strategy within our POSGI model with five other strategies commonly used in similar markets show that the CE strategy results in improved price predictions and higher utilities to the agents as compared to other strategies.