The design of efficient solutions for abstract argumentation problems is a
crucial step towards advanced argumentation systems. One of the most prominent
approaches in the literature is to use Answer-Set Programming (ASP) for this
endeavor. In this paper, we present new encodings for three prominent
argumentation semantics using the concept of conditional literals in
disjunctions as provided by the ASP-system clingo. Our new encodings are not
only more succinct than previous versions, but also outperform them on standard
benchmarks.

本文使用 ASP 系统 clingo 提供的条件量词的析取形式，提供了三种著名的辩论语义的新编码，这些编码不仅比以前的版本更简洁，而且在标准基准测试中也表现优异，从而为高级辩论系统的高效解决方案的设计提供了一步关键。

针对抽象论证的改进答案集编程编码

Improved Answer-Set Programming Encodings for Abstract Argumentation

Input languages of answer set solvers are based on the mathematically simple
concept of a stable model. But many useful constructs available in these
languages, including local variables, conditional literals, and aggregates,
cannot be easily explained in terms of stable models in the sense of the
original definition of this concept and its straightforward generalizations.
Manuals written by designers of answer set solvers usually explain such
constructs using examples and informal comments that appeal to the user's
intuition, without references to any precise semantics. We propose to approach
the problem of defining the semantics of gringo programs by translating them
into the language of infinitary propositional formulas. This semantics allows
us to study equivalent transformations of gringo programs using natural
deduction in infinitary propositional logic.

该研究通过将答案集求解器转换为无穷命题公式的语言，解决了一些基于本质稳定模型定义的复杂结构，如局部变量、条件文字和聚合等，避免了纯手动的解释。