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Higher-Order Decision Theory

  • Jules Hedges
  • Paulo Oliva
  • Evguenia Shprits
  • Viktor Winschel
  • Philipp Zahn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10576)

Abstract

This paper investigates a surprising relationship between decision theory and proof theory. Using constructions originating in proof theory based on higher-order functions, so called quantifiers and selection functions, we show that these functionals model choice behavior of individual agents. Our framework is expressive, it captures classical theories such as utility functions and preference relations but it can also be used to faithfully model abstract goals such as coordination. It is directly implementable in functional programming languages. Lastly, modeling an agent with selection functions and quantifiers is modular and thereby allows to seamlessly combine agents bridging decision theory and game theory.

Keywords

Decision theory Utility functions Preferences Higher-order functions Quantifiers 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jules Hedges
    • 1
  • Paulo Oliva
    • 2
  • Evguenia Shprits
    • 3
  • Viktor Winschel
    • 4
  • Philipp Zahn
    • 5
  1. 1.Department of Computer ScienceUniversity of OxfordOxfordUK
  2. 2.Department of Electronic Engineering and Computer ScienceQueen Mary University of LondonLondonUK
  3. 3.Department of EconomicsUniversity of MannheimMannheimGermany
  4. 4.OICOS GmbHMannheimGermany
  5. 5.Department of EconomicsUniversity of St. GallenSt. GallenSwitzerland

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