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Estimating Auction Equilibria using Individual Evolutionary Learning

I develop the Generalized Evolutionary Nash Equilibrium Estimator (GENEE) library. The tool is designed to provide a generic computational library for running genetic algorithms and individual evolutionary learning in economic decision-making environments. Most importantly, I have adapted the library to estimate equilibria bidding functions in auctions. I show it produces highly accurate estimates across a large class of auction environments with known solutions. I then apply GENEE to estimate the equilibria of two additional auctions with no known solutions: first-price sealed-bid common value auctions with multiple signals, and simultaneous first-price auctions with subadditive values

Identiferoai:union.ndltd.org:chapman.edu/oai:digitalcommons.chapman.edu:cads_dissertations-1000
Date31 May 2019
CreatorsJames, Kevin
PublisherChapman University Digital Commons
Source SetsChapman University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceComputational and Data Sciences (Ph.D.) Dissertations
Rightshttp://creativecommons.org/licenses/by/4.0/

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