swMATH ID: 18512
Software Authors: Nickles, Matthias
Description: A tool for probabilistic reasoning based on logic programming and first-order theories under stable model semantics. 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).
Homepage: http://link.springer.com/chapter/10.1007%2F978-3-319-48758-8_24
Keywords: artificial intelligence; answer set programming; probabilistic logic programming; statistical-relational learning; sat
Related Software: PRISM; ProbLog; DeepProbLog; cplint; SCIFF; XSB; CP-logic; SOLAR; Datalog; f2lp
Cited in: 3 Publications

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