ML Anthology

State-Space Planning by Integer Optimization

Henry A. Kautz, Joachim P. Walser
AAAI 1999 pp. 526-533
/aaai/1999/kautz1999aaai-state/

Abstract

This paper describes ILP-PLAN, a framework for solving AI planning problems represented as integer linear programs. ILP-PLAN extends the planning as satisfiability framework to handle plans with resources, action costs, and complex ob-jective functions. We show that challenging planning prob-lems can be effectively solved using both traditional branch-and-bound IP solvers and efficient new integer local search algorithms. ILP-PLAN can find better quality solutions for a set of hard benchmark logistics planning problems than had been found by any earlier system. 1

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Cite

Text

Kautz and Walser. "State-Space Planning by Integer Optimization." AAAI Conference on Artificial Intelligence, 1999.

Markdown

[Kautz and Walser. "State-Space Planning by Integer Optimization." AAAI Conference on Artificial Intelligence, 1999.](https://mlanthology.org/aaai/1999/kautz1999aaai-state/)

BibTeX

@inproceedings{kautz1999aaai-state,
  title     = {{State-Space Planning by Integer Optimization}},
  author    = {Kautz, Henry A. and Walser, Joachim P.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1999},
  pages     = {526-533},
  url       = {https://mlanthology.org/aaai/1999/kautz1999aaai-state/}
}