English

Conformant Planning as a Case Study of Incremental QBF Solving

Logic in Computer Science 2016-04-05 v3 Artificial Intelligence

Abstract

We consider planning with uncertainty in the initial state as a case study of incremental quantified Boolean formula (QBF) solving. We report on experiments with a workflow to incrementally encode a planning instance into a sequence of QBFs. To solve this sequence of incrementally constructed QBFs, we use our general-purpose incremental QBF solver DepQBF. Since the generated QBFs have many clauses and variables in common, our approach avoids redundancy both in the encoding phase and in the solving phase. Experimental results show that incremental QBF solving outperforms non-incremental QBF solving. Our results are the first empirical study of incremental QBF solving in the context of planning and motivate its use in other application domains.

Keywords

Cite

@article{arxiv.1405.7253,
  title  = {Conformant Planning as a Case Study of Incremental QBF Solving},
  author = {Uwe Egly and Martin Kronegger and Florian Lonsing and Andreas Pfandler},
  journal= {arXiv preprint arXiv:1405.7253},
  year   = {2016}
}

Comments

added reference to extended journal article; revision (camera-ready, to appear in the proceedings of AISC 2014, volume 8884 of LNAI, Springer)

R2 v1 2026-06-22T04:25:11.781Z