比较四种非极小化析取语义，发现三者等价且强于经典逻辑处理方式。
Comparing Non-minimal Semantics for Disjunction in Answer Set Programming
- 提出三种非极小语义并证明其等价性，统一不同定义下的析取处理。
- 新语义始终包含所有稳定模型，且严格强于强支持模型。
- 适合逻辑编程、知识表示研究者，关注析取语义的理论边界。
本文比较了答案集编程中四种不满足模型极小性原则的析取语义。其中两种（Cabalar和Muñiz的合理模型、Doherty和Szalas的强支持模型）直接提供非极小析取语义；另两种（Aguado等的分叉语义、Shen和Eiter的确定性推理语义）虽引入新析取算子，但在此被视作标准析取算子的新语义。我们证明：分叉语义、合理模型与合理松弛后的确定性推理语义三者实际等价，构成同一语义的不同表述。该共同语义始终为程序稳定模型的超集（在任意上下文中），且严格强于强支持模型，后者将析取视为经典逻辑处理。
原文摘要 · Abstract (English)
In this paper, we compare four different semantics for disjunction in Answer Set Programming that, unlike stable models, do not adhere to the principle of model minimality. Two of these approaches, Cabalar and Muñiz' \emph{Justified Models} and Doherty and Szalas' \emph{Strongly Supported Models}, directly provide an alternative non-minimal semantics for disjunction. The other two, Aguado et al's \emph{Forks} and Shen and Eiter's \emph{Determining Inference} (DI) semantics, actually introduce a new disjunction connective, but are compared here as if they constituted new semantics for the standard disjunction operator. We are able to prove that three of these approaches (Forks, Justified Models and a reasonable relaxation of the DI semantics) actually coincide, constituting a common single approach under different definitions. Moreover, this common semantics always provides a superset of the stable models of a program (in fact, modulo any context) and is strictly stronger than the fourth approach (Strongly Supported Models), that actually treats disjunctions as in classical logic.
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