## Abstract

Stochastic boolean function evaluation (SBFE) is the problem of determining the value of a given boolean function f on an unknown input x, when each bit x_{i} of x can only be determined by paying a given associated cost c_{i}. Further, x is drawn from a given product distribution: for each x_{i}, Pr[ x_{i}= 1 ] = p_{i} and the bits are independent. The goal is to minimize the expected cost of evaluation. In this paper, we study the complexity of the SBFE problem for classes of DNF formulas. We consider both exact and approximate versions of the problem for subclasses of DNF, for arbitrary costs and product distributions, and for unit costs and/or the uniform distribution.

Original language | English (US) |
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Pages (from-to) | 661-685 |

Number of pages | 25 |

Journal | Algorithmica |

Volume | 77 |

Issue number | 3 |

DOIs | |

State | Published - Mar 1 2017 |

## Keywords

- Approximation algorithms
- DNF formulas
- Sequential testing
- Stochastic boolean function evaluation

## ASJC Scopus subject areas

- General Computer Science
- Computer Science Applications
- Applied Mathematics