Full metadata
Title
Answer set programming and other computing paradigms
Description
Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to its modeling language in order to enhance expressivity, such as incorporating aggregates and interfaces with ontologies. Also, in order to overcome the grounding bottleneck of computation in ASP, there are increasing interests in integrating ASP with other computing paradigms, such as Constraint Programming (CP) and Satisfiability Modulo Theories (SMT). Due to the non-monotonic nature of the ASP semantics, such enhancements turned out to be non-trivial and the existing extensions are not fully satisfactory. We observe that one main reason for the difficulties rooted in the propositional semantics of ASP, which is limited in handling first-order constructs (such as aggregates and ontologies) and functions (such as constraint variables in CP and SMT) in natural ways. This dissertation presents a unifying view on these extensions by viewing them as instances of formulas with generalized quantifiers and intensional functions. We extend the first-order stable model semantics by by Ferraris, Lee, and Lifschitz to allow generalized quantifiers, which cover aggregate, DL-atoms, constraints and SMT theory atoms as special cases. Using this unifying framework, we study and relate different extensions of ASP. We also present a tight integration of ASP with SMT, based on which we enhance action language C+ to handle reasoning about continuous changes. Our framework yields a systematic approach to study and extend non-monotonic languages.
Date Created
2013
Contributors
- Meng, Yunsong (Author)
- Lee, Joohyung (Thesis advisor)
- Ahn, Gail-Joon (Committee member)
- Baral, Chitta (Committee member)
- Fainekos, Georgios (Committee member)
- Lifschitz, Vladimir (Committee member)
- Arizona State University (Publisher)
Topical Subject
- Computer Science
- Information Technology
- answer set programming
- artificial intelligence
- Framework for Integration
- Knowledge Representation and Reasoning
- Logic programming
- Stable Model
- Logic programming
- Knowledge representation (Information theory)
- artificial intelligence
- Constraint programming (Computer science)
Resource Type
Extent
xi, 272 p. : ill
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.17828
Statement of Responsibility
by Yunsong Meng
Description Source
Viewed on Nov. 14, 2013
Level of coding
full
Note
thesis
Partial requirement for: Ph.D., Arizona State University, 2013
bibliography
Includes bibliographical references (p. 263-272)
Field of study: Computer science
System Created
- 2013-07-12 06:19:20
System Modified
- 2021-08-30 01:42:14
- 3 years 3 months ago
Additional Formats