TY - GEN

T1 - Cost-based query answering in action probabilistic logic programs

AU - Simari, Gerardo I.

AU - Dickerson, John P.

AU - Subrahmanian, V. S.

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=77958040753&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77958040753&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-15951-0_30

DO - 10.1007/978-3-642-15951-0_30

M3 - Conference contribution

AN - SCOPUS:77958040753

SN - 3642159508

SN - 9783642159503

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 319

EP - 332

BT - Scalable Uncertainty Management - 4th International Conference, SUM 2010, Proceedings

T2 - 4th International Conference on Scalable Uncertainty Management, SUM 2010

Y2 - 27 September 2010 through 29 September 2010

ER -