Knowledge Forgetting in Circumscription: A Preliminary Report
Authors: Yisong Wang, Kewen Wang, Zhe Wang, Zhiqiang Zhuang
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper a theory of forgetting for propositional circumscription is proposed, which is not a straightforward adaption of existing approaches. In particular, some properties that are essential for existing proposals do not hold any longer or have to be reformulated. Several useful properties of the new forgetting are proved, which demonstrate suitability of the forgetting for circumscription. A sound and complete algorithm for the forgetting is developed and an analysis of computational complexity is given. |
| Researcher Affiliation | Academia | Yisong Wang Department of Computer Science, Guizhou University, 550025, China Kewen Wang and Zhe Wang and Zhiqiang Zhuang School of Information and Communication Technology, Griffith University, QLD 4111, Australia |
| Pseudocode | Yes | Algorithm 1: Computing [P; Q]-forgetting result Input : A formula ϕ(P, Q) and V A Output: A result of [P; Q]-forgetting V from ϕ 1 M Mod(CIRC[ϕ; P; Q]) V ; 2 foreach M s.t. M |= ϕ and M / M do 3 if M M such that M <P ;Q M V then 4 M M {M V }; 7 ψ W M M V(M (V \ M)) ; 8 return ψ; |
| Open Source Code | No | The paper does not provide any specific links or statements about the availability of open-source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and presents logical formalisms and proofs. It does not use empirical datasets for training or evaluation. Examples used are symbolic, such as 'bird(tweety)' or propositional formulas like 'p q r'. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical validation on datasets, thus no training/validation/test splits are mentioned. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup that would require specific hardware. No hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe any experimental implementation details that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe empirical experiments. Therefore, no experimental setup details, hyperparameters, or training configurations are provided. |