TY - GEN
T1 - A tool for probabilistic reasoning based on logic programming and first-order theories under stable model semantics
AU - Nickles, Matthias
N1 - Publisher Copyright:
© Springer International Publishing AG 2016.
PY - 2016
Y1 - 2016
N2 - This System Description paper describes the software framework PrASP (“Probabilistic Answer Set Programming”). PrASP is both an uncertainty reasoning and machine learning software and a probabilistic logic programming language based on Answer Set Programming (ASP). Besides serving as a research software platform for non-monotonic (inductive) probabilistic logic programming, our framework mainly targets applications in the area of uncertainty stream reasoning. PrASP programs can consist of ASP (AnsProlog) as well as First-Order Logic formulas (with stable model semantics), annotated with conditional or unconditional probabilities or probability intervals. A number of alternative inference algorithms allow to attune the system to different task characteristics (e.g., whether or not independence assumptions can be made).
AB - This System Description paper describes the software framework PrASP (“Probabilistic Answer Set Programming”). PrASP is both an uncertainty reasoning and machine learning software and a probabilistic logic programming language based on Answer Set Programming (ASP). Besides serving as a research software platform for non-monotonic (inductive) probabilistic logic programming, our framework mainly targets applications in the area of uncertainty stream reasoning. PrASP programs can consist of ASP (AnsProlog) as well as First-Order Logic formulas (with stable model semantics), annotated with conditional or unconditional probabilities or probability intervals. A number of alternative inference algorithms allow to attune the system to different task characteristics (e.g., whether or not independence assumptions can be made).
KW - Answer set programming
KW - Artificial intelligence
KW - Probabilistic logic programming
KW - SAT
KW - Statistical-relational learning
UR - https://www.scopus.com/pages/publications/84995653366
U2 - 10.1007/978-3-319-48758-8_24
DO - 10.1007/978-3-319-48758-8_24
M3 - Conference Publication
AN - SCOPUS:84995653366
SN - 9783319487571
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 369
EP - 384
BT - Logics in Artificial Intelligence - 15th European Conference, JELIA 2016, Proceedings
A2 - Kakas, Antonis
A2 - Michael, Loizos
PB - Springer-Verlag
T2 - 15th European Conference on Logics in Artificial Intelligence, JELIA 2016
Y2 - 9 November 2016 through 11 November 2016
ER -