Partially observable stochastic game-based multi-agent prediction markets

Janyl Jumadinova, Prithviraj Dasgupta

Research output: Contribution to conferencePaper

2 Scopus citations

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.

Original languageEnglish (US)
Pages1149-1150
Number of pages2
StatePublished - Jan 1 2011
Event10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 - Taipei, Taiwan, Province of China
Duration: May 2 2011May 6 2011

Conference

Conference10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011
CountryTaiwan, Province of China
CityTaipei
Period5/2/115/6/11

Keywords

  • Correlated equilibrium
  • Prediction market
  • Stochastic game

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Jumadinova, J., & Dasgupta, P. (2011). Partially observable stochastic game-based multi-agent prediction markets. 1149-1150. Paper presented at 10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011, Taipei, Taiwan, Province of China.