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Recent Progress in Proof Mining in Nonlinear Analysis.

Journal Article Number 10 Logic in Computer Science

Abstract

During the last two decades the program of ‘proof mining’ emerged which uses tools from mathematical logic (so-called proof interpretations) to systematically extract explicit quantitative information (e.g. rates of convergence) from prima facie nonconstructive proofs (e.g. convergence proofs). This has been applied particularly successful in the context of nonlinear analysis: fixed point theory, ergodic theory, topological dynamics, convex optimization and abstract Cauchy problems. In this paper we give a survey on some of the results, both on the logical foundation of proof mining as well as its applications in nonlinear analysis, obtained since the monograph [65] appeared.

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Context

Venue
IfCoLog Journal of Logics and their Applications
Archive span
2014-2026
Indexed papers
633
Paper id
502478610083135618
v2026.09.13