rconfalonieri / pospsmodels Goto Github PK
View Code? Open in Web Editor NEWUncertainty and Preference-Aware Solver Based on Answer Set Programming
Uncertainty and Preference-Aware Solver Based on Answer Set Programming
posPsmodels-v0.1 -------------- PosPsmodels is an ASP-based solver (in beta version) able to process logic programs with possibilsitic ordered disjunction (or LPPODs). LPPODs are a generalisation of LPODs and they are class of programs which can reason about preferences and uncertainty. PosPsmodels can be used to compute possibilistic preferred answer sets under LPPODs semantics. The semantics is implemented by means of a syntactic reduction and a fix-point operator used to compute possibilistic normal logic programs. Pospsmodels needs lparse, psmodels, and possModels (and therefore smodels v2.28). Usage: computeLppod/./posPsmodels lppod/input_file For example, given the LPPOD program dessert.lppod: 60 ice_cream x cake. 40 coffee x tea. 100 :- ice_cream, coffee. we can compute all possibilistic preferred stable models with: % (let's assume we are in the computeLppod folder) % ./posPsmodels lppod/dessert.lppod The resulting answer is: ******** Possibilistic Model 1*********** (coffee,40) (cake,60) [Rule_id,sat_degree]: [1,2] [2,1] [Rule_id,Necessity_degree]: [1,60] [2,40] [Rule_id,Rule]: 1, 60 ice_cream x cake . [Rule_id,Rule]: 2, 40 coffee x tea . Was Best LpodModel 1 *************************************************** ******** Possibilistic Model 3*********** (tea,40) (ice_cream,60) [Rule_id,sat_degree]: [1,1] [2,2] [Rule_id,Necessity_degree]: [1,60] [2,40] [Rule_id,Rule]: 1, 60 ice_cream x cake . [Rule_id,Rule]: 2, 40 coffee x tea . Was Best LpodModel 1 *************************************************** ******** Possibilistic Model 2*********** (tea,40) (cake,60) [Rule_id,sat_degree]: [1,2] [2,2] [Rule_id,Necessity_degree]: [1,60] [2,40] [Rule_id,Rule]: 1, 60 ice_cream x cake . [Rule_id,Rule]: 2, 40 coffee x tea . Was Best LpodModel 1 *************************************************** As we see, there are three possibilistic preferred models. Possibilistic Model 1 and Possibilistic Model 3 are equally preferred by the satisfaction degrees but Possibilistic Model 3 is possibilistically preferred to Possibilistic Model 1. Possibilistic Model 2 is a third choice. Syntax ------ Basically everything that goes through lparse should work also with posPsmodels but since this is a first prototype, it might be a good idea to refrain from using more esoteric stuff. The basic syntax is as follows: (0..100] a x b :- body. % a basic possibilistic ordered disjunction rule where (0..100] means an integer belonging to (0,100], and Ôa x b :- bodyÕ is an ordered disjunction rule. Informally it means that if body is true, then a should be certain at least at level alpha. If a canÕt be true, then b has to be certain at least alpha. The formal definition can be found in: Confalonieri, R., Nieves, J.C., Osorio, M., V‡zquez-Salceda, J. Possibilistic Semantics for Logic Programs with Ordered Disjunction. In: Foundations of Information and Knowledge Systems (Prade, H., Link, S., eds.), LNCS vol. 5956, pp. 133-152, Springer, (2010). The posPsmodels distribution archive contains a README file that explains how to get ready with the solver. The solver is in beta release and it has been tested for OS X systems only. Roberto Confalonieri [email protected]
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.