Higher order interpretation for higher order complexity

17 pages•Published: May 4, 2017

Abstract

We design an interpretation-based theory of higher-order functions that is well-suited for the complexity analysis of a standard higher- order functional language a` la ml. We manage to express the interpretation of a given program in terms of a least fixpoint and we show that when restricted to functions bounded by higher-order polynomials, they characterize exactly classes of tractable functions known as Basic Feasible Functions at any order.

Keyphrases: basic feasible functionals, higher order complexity, interpretations

In: Thomas Eiter and David Sands (editors). LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning, vol 46, pages 269-285.

Links:	https://easychair.org/publications/paper/7F
	https://doi.org/10.29007/1tkw

BibTeX entry

@inproceedings{LPAR-21:Higher_order_interpretation_higher,
  author    = {Emmanuel Hainry and Romain Péchoux},
  title     = {Higher order interpretation for higher order complexity},
  booktitle = {LPAR-21. 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning},
  editor    = {Thomas Eiter and David Sands},
  series    = {EPiC Series in Computing},
  volume    = {46},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/7F},
  doi       = {10.29007/1tkw},
  pages     = {269-285},
  year      = {2017}}

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