Abstract
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).
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Notes
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- 2.
PrASP’s default ASP grounder/solver Clingo also allows for function symbols, but for simplicity we ignore functions in the rest of this section.
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- 4.
Not related to the Iterative Refinement method in linear systems solving.
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Nickles, M. (2016). A Tool for Probabilistic Reasoning Based on Logic Programming and First-Order Theories Under Stable Model Semantics. In: Michael, L., Kakas, A. (eds) Logics in Artificial Intelligence. JELIA 2016. Lecture Notes in Computer Science(), vol 10021. Springer, Cham. https://doi.org/10.1007/978-3-319-48758-8_24
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