Cost-based query answering in action probabilistic logic programs

Gerardo I. Simari, John P. Dickerson, V. S. Subrahmanian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


Action-probabilistic logic programs (ap-programs), a class of probabilistic logic programs, have been applied during the last few years for modeling behaviors of entities. Rules in ap-programs have the form "If the environment in which entity E operates satisfies certain conditions, then the probability that E will take some action A is between L and U". Given an ap-program, we have addressed the problem of deciding if there is a way to change the environment (subject to some constraints) so that the probability that entity E takes some action (or combination of actions) is maximized. In this work we tackle a related problem, in which we are interested in reasoning about the expected reactions of the entity being modeled when the environment is changed. Therefore, rather than merely deciding if there is a way to obtain the desired outcome, we wish to find the best way to do so, given costs of possible outcomes. This is called the Cost-based Query Answering Problem (CBQA). We first formally define and study an exact (intractable) approach to CBQA, and then go on to propose a more efficient algorithm for a specific subclass of ap-programs that builds on past work in a basic version of this problem.

Original languageEnglish (US)
Title of host publicationScalable Uncertainty Management - 4th International Conference, SUM 2010, Proceedings
Number of pages14
StatePublished - 2010
Externally publishedYes
Event4th International Conference on Scalable Uncertainty Management, SUM 2010 - Toulouse, France
Duration: Sep 27 2010Sep 29 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6379 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th International Conference on Scalable Uncertainty Management, SUM 2010

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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