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The Max-Plus Martin Boundary

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Abstract

We develop an idempotent version of probabilistic potential theory. The goal is to describe the set of max-plus harmonic functions, which give the stationary solutions of deterministic optimal control problems with additive reward. The analogue of the Martin compactification is seen to be a generalisation of the compactification of metric spaces using (generalised) Busemann functions. We define an analogue of the minimal Martin boundary and show that it can be identified with the set of limits of “almost-geodesics”, and also the set of (normalised) harmonic functions that are extremal in the max-plus sense. Our main result is a max-plus analogue of the Martin representation theorem, which represents harmonic functions by measures supported on the minimal Martin boundary. We illustrate it by computing the eigenvectors of a class of Lax-Oleinik semigroups with nondifferentiable Lagrangian: we relate extremal eigenvector to Busemann points of normed spaces.

Original languageEnglish
Pages (from-to)195-240
Number of pages46
JournalDocumenta Mathematica
Volume14
DOIs
Publication statusPublished - 1 Jan 2009

Keywords

  • Busemann functions
  • Lax-Oleinik semigroup
  • Markov decision process
  • Martin boundary
  • deterministic optimal control
  • dynamic programming
  • eigenvalues
  • eigenvectors
  • extremal generators
  • max-plus algebra
  • metric boundary
  • potential theory
  • weak KAM solutions

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