KDGT: Knowledge Discovery in Game Theory

Games have been used with astounding success to describe diverse situations where one or more entities (players) interact with each other according to various rules. As the concept is encompassing, it is very flexible and that is the reason why applications range from the social sciences and economi...

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Bibliographic Details
Published in2009 Second International Workshop on Knowledge Discovery and Data Mining pp. 261 - 264
Main Authors Ganesh Ganesh, M., Sunke, A., Ganesh, S., Avinesh, D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2009
Subjects
Application software
Biological system modeling
Biology computing
Computer science
Data mining
Economic forecasting
Educational institutions
Game theory
Games
Mathematics
Players
Power generation economics
Utility
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Summary:Games have been used with astounding success to describe diverse situations where one or more entities (players) interact with each other according to various rules. As the concept is encompassing, it is very flexible and that is the reason why applications range from the social sciences and economics to biology and mathematics or computer science. This makes the game theoretic computation very complicated. This research work presents a frame work which integrates game theory with data mining. Due to enormous amount of data, it is hard for game theory alone to perform the modeling analysis. Data mining assists game theory to deal with the large amount of data and finds hidden rules to improve game analysis.
ISBN:9780769535432
0769535437
DOI:10.1109/WKDD.2009.220