A multi-agent prediction market based on Boolean network evolution

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Prediction markets have been shown to be a useful tool in forecasting the outcome of future events by aggregating public opinion about the events' outcome. Previous research on prediction markets has mostly analyzed the prediction markets by building complex analytical models. In this paper, we posit that simpler yet powerful Boolean rules can be used to adequately describe the operations of a prediction market. We have used a multi-agent based prediction market where Boolean network based rules are used to capture the evolution of the beliefs of the market's participants, as well as to aggregate the prices in the market. We show that despite the simplification of the traders' beliefs in the prediction market into Boolean states, the aggregated market price calculated using our BN model is strongly correlated with the price calculated by a commonly used aggregation strategy in existing prediction markets called the Logarithmic Market Scoring Rule (LMSR). We also empirically show that our Boolean network-based prediction market can stabilize market prices under the presence of untruthful belief revelation by the traders.

Original languageEnglish (US)
Title of host publicationProceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011
Pages171-179
Number of pages9
DOIs
StatePublished - Nov 7 2011
Event2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011 - Lyon, France
Duration: Aug 22 2011Aug 27 2011

Publication series

NameProceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011
Volume2

Conference

Conference2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011
CountryFrance
CityLyon
Period8/22/118/27/11

Fingerprint

Analytical models
Agglomeration

Keywords

  • Boolean networks
  • Complex systems modeling
  • Distributed information aggregation
  • Prediction markets

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Jumadinova, J., Matache, M. T., & Dasgupta, P. (2011). A multi-agent prediction market based on Boolean network evolution. In Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011 (pp. 171-179). [6040773] (Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011; Vol. 2). https://doi.org/10.1109/WI-IAT.2011.228

A multi-agent prediction market based on Boolean network evolution. / Jumadinova, Janyl; Matache, Mihaela T.; Dasgupta, Prithviraj.

Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011. 2011. p. 171-179 6040773 (Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011; Vol. 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jumadinova, J, Matache, MT & Dasgupta, P 2011, A multi-agent prediction market based on Boolean network evolution. in Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011., 6040773, Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011, vol. 2, pp. 171-179, 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011, Lyon, France, 8/22/11. https://doi.org/10.1109/WI-IAT.2011.228
Jumadinova J, Matache MT, Dasgupta P. A multi-agent prediction market based on Boolean network evolution. In Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011. 2011. p. 171-179. 6040773. (Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011). https://doi.org/10.1109/WI-IAT.2011.228
Jumadinova, Janyl ; Matache, Mihaela T. ; Dasgupta, Prithviraj. / A multi-agent prediction market based on Boolean network evolution. Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011. 2011. pp. 171-179 (Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011).
@inproceedings{6923fed25f844c678236ed3a546fdea1,
title = "A multi-agent prediction market based on Boolean network evolution",
abstract = "Prediction markets have been shown to be a useful tool in forecasting the outcome of future events by aggregating public opinion about the events' outcome. Previous research on prediction markets has mostly analyzed the prediction markets by building complex analytical models. In this paper, we posit that simpler yet powerful Boolean rules can be used to adequately describe the operations of a prediction market. We have used a multi-agent based prediction market where Boolean network based rules are used to capture the evolution of the beliefs of the market's participants, as well as to aggregate the prices in the market. We show that despite the simplification of the traders' beliefs in the prediction market into Boolean states, the aggregated market price calculated using our BN model is strongly correlated with the price calculated by a commonly used aggregation strategy in existing prediction markets called the Logarithmic Market Scoring Rule (LMSR). We also empirically show that our Boolean network-based prediction market can stabilize market prices under the presence of untruthful belief revelation by the traders.",
keywords = "Boolean networks, Complex systems modeling, Distributed information aggregation, Prediction markets",
author = "Janyl Jumadinova and Matache, {Mihaela T.} and Prithviraj Dasgupta",
year = "2011",
month = "11",
day = "7",
doi = "10.1109/WI-IAT.2011.228",
language = "English (US)",
isbn = "9780769545134",
series = "Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011",
pages = "171--179",
booktitle = "Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011",

}

TY - GEN

T1 - A multi-agent prediction market based on Boolean network evolution

AU - Jumadinova, Janyl

AU - Matache, Mihaela T.

AU - Dasgupta, Prithviraj

PY - 2011/11/7

Y1 - 2011/11/7

N2 - Prediction markets have been shown to be a useful tool in forecasting the outcome of future events by aggregating public opinion about the events' outcome. Previous research on prediction markets has mostly analyzed the prediction markets by building complex analytical models. In this paper, we posit that simpler yet powerful Boolean rules can be used to adequately describe the operations of a prediction market. We have used a multi-agent based prediction market where Boolean network based rules are used to capture the evolution of the beliefs of the market's participants, as well as to aggregate the prices in the market. We show that despite the simplification of the traders' beliefs in the prediction market into Boolean states, the aggregated market price calculated using our BN model is strongly correlated with the price calculated by a commonly used aggregation strategy in existing prediction markets called the Logarithmic Market Scoring Rule (LMSR). We also empirically show that our Boolean network-based prediction market can stabilize market prices under the presence of untruthful belief revelation by the traders.

AB - Prediction markets have been shown to be a useful tool in forecasting the outcome of future events by aggregating public opinion about the events' outcome. Previous research on prediction markets has mostly analyzed the prediction markets by building complex analytical models. In this paper, we posit that simpler yet powerful Boolean rules can be used to adequately describe the operations of a prediction market. We have used a multi-agent based prediction market where Boolean network based rules are used to capture the evolution of the beliefs of the market's participants, as well as to aggregate the prices in the market. We show that despite the simplification of the traders' beliefs in the prediction market into Boolean states, the aggregated market price calculated using our BN model is strongly correlated with the price calculated by a commonly used aggregation strategy in existing prediction markets called the Logarithmic Market Scoring Rule (LMSR). We also empirically show that our Boolean network-based prediction market can stabilize market prices under the presence of untruthful belief revelation by the traders.

KW - Boolean networks

KW - Complex systems modeling

KW - Distributed information aggregation

KW - Prediction markets

UR - http://www.scopus.com/inward/record.url?scp=80155135490&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80155135490&partnerID=8YFLogxK

U2 - 10.1109/WI-IAT.2011.228

DO - 10.1109/WI-IAT.2011.228

M3 - Conference contribution

AN - SCOPUS:80155135490

SN - 9780769545134

T3 - Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011

SP - 171

EP - 179

BT - Proceedings - 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011

ER -