Resilient Logic Programs: Answer Set Programs Challenged by Ontologies
Authors: Sanja Lukumbuzya, Magdalena Ortiz, Mantas Šimkus2917-2924
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We introduce resilient logic programs (RLPs) that couple a non-monotonic logic program and a first-order (FO) theory or description logic (DL) ontology. Unlike previous hybrid languages, where the interaction between the program and the theory is limited to consistency or query entailment tests, in RLPs answer sets must be resilient to the models of the theory, allowing non-output predicates of the program to respond differently to different models. RLPs can elegantly express -QBFs, disjunctive ASP, and configuration problems under incompleteness of information. RLPs are decidable when a couple of natural assumptions are made: (i) satisfiability of FO theories in the presence of closed predicates is decidable, and (ii) rules are safe in the style of the well-known DL-safeness. We further show that a large fragment of such RLPs can be translated into standard (disjunctive) ASP, for which efficient implementations exist. For RLPs with theories expressed in DLs, we use a novel relaxation of safeness that safeguards rules via predicates whose extensions can be inferred to have a finite bound. We present several complexity results for the case where ontologies are written in some standard DLs. |
| Researcher Affiliation | Academia | Sanja Lukumbuzya, Magdalena Ortiz, Mantas ˇSimkus Institute of Logic and Computation, TU Wien, Austria {lukumbuzya, ortiz}@kr.tuwien.ac.at, simkus@dbai.tuwien.ac.at |
| Pseudocode | Yes | Algorithm 1: Answer set existence of RLPs. Algorithm has Answer Set(Π) Input : RLP Π = (P, T , Σout, Σowa, Σre) Output: true iff Π has an answer Guess an interpretation I over Σout and adom(P) return is Consistent(T , I, Σout) and not has CE(I, Π, adom(P), Σout) Subroutine has CE(I, Π, Δ, B) Input : Interpretation I, RLP Π = (P, T , Σout, Σowa, Σre), Δ Sconst, and B sig(T ) Output: true iff there is a counter example to I being an answer set of Π Guess an interpretation J over sig(P) sig(T ) Σout and the constants from Δ s.t. J|Σout = I|Σout J J { p( c) | c Δart(p), p sig(P) (sig(T ) ), and p( c) J} return is Consistent(T , J , B) and not has Resp(J, Π) Subroutine has Resp(J, Π) Input : Interpretation J, RLP Π = (P, T , Σout, Σowa, Σre) Output: true iff there exists a response to J w.r.t. J|Σout and Π Guess an interpretation H over sig(P) and the constants from J and adom(P) s.t. H|Σout Σowa = J return H|Σout Σre is a min. model of PH,Σowa |
| Open Source Code | No | The paper does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not involve the use of datasets for training or evaluation. No information regarding public dataset availability is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe any specific hardware used for running experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers needed to replicate the theoretical framework or algorithms discussed. |
| Experiment Setup | No | The paper is theoretical and does not include details on experimental setup such as hyperparameters or training configurations. |