Knowledge Forgetting in Answer Set Programming
Authors: Y. Wang, Y. Zhang, Y. Zhou, M. Zhang
JAIR 2014 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we uniformly propose a semantic knowledge forgetting, called HTand FLP-forgetting, for logic programs under stable model and FLP-stable model semantics, respectively. Our proposed knowledge forgetting discards exactly the knowledge of a logic program which is relevant to forgotten variables. Thus it preserves strong equivalence in the sense that strongly equivalent logic programs will remain strongly equivalent after forgetting the same variables. We show that this semantic forgetting result is always expressible; and we prove a representation theorem stating that the HTand FLP-forgetting can be precisely characterized by Zhang-Zhou s four forgetting postulates under the HTand FLP-model semantics, respectively. We also reveal underlying connections between the proposed forgetting and the forgetting of propositional logic, and provide complexity results for decision problems in relation to the forgetting. An application of the proposed forgetting is also considered in a conflict solving scenario. |
| Researcher Affiliation | Academia | Yisong Wang EMAIL Department of Computer Science, Guizhou University, Guiyang, China Yan Zhang EMAIL Yi Zhou EMAIL Artificial Intelligence Research Group, University of Western Sydney, Australia Mingyi Zhang EMAIL Guizhou Academy of Sciences, Guiyang, China |
| Pseudocode | Yes | Wong also defined two forgetting operators FS and FW: the result of forgetting an atom a from a disjunctive logic program Π is defined by the below procedure: (1) Let Π1 = Cn(Π). (2) Form Π1, remove rules of the form (A B, a, not C), replace each rule of the form (A {a} B, not C, not a) with (A B, not C, not a). Let the resulting logic program be Π2. (3) Replace or remove each rule in Π2, of the form (A B, not C, not a) or (A {a} B, not C) according to the following table: |
| Open Source Code | No | The paper does not provide any explicit statements about making source code available, nor does it include links to code repositories in the main text or supplementary materials. |
| Open Datasets | No | The paper primarily focuses on theoretical aspects of knowledge forgetting in Answer Set Programming. It uses examples like the 'Yale Shooting scenario' and a 'family investment plan' in a conflict-solving scenario (Example 9), but these are illustrative examples for theoretical concepts rather than actual datasets used for empirical evaluation. No specific links, DOIs, repositories, or citations for publicly available datasets are provided. |
| Dataset Splits | No | The paper is theoretical and does not describe any experimental evaluations using datasets. Therefore, it does not provide information on dataset splits such as training, validation, or test sets. |
| Hardware Specification | No | The paper presents theoretical work on knowledge forgetting in Answer Set Programming and does not describe any experiments requiring specific hardware. Therefore, no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and focuses on logic programs and their semantics. It mentions specific software (CPLEX, Gecode, Choco) in a general discussion about other work (e.g., Lang et al., 2003) but does not list any specific software dependencies with version numbers for its own proposed methodology or any accompanying empirical work. |
| Experiment Setup | No | The paper is theoretical and introduces new concepts, theorems, and properties related to knowledge forgetting in logic programs. It does not describe any experimental setups, hyperparameter values, or training configurations. |