We present an extension-based approach for computing and verifying
preferences in an abstract argumentation system. Although numerous
argumentation semantics have been developed previously for identifying
acceptable sets of arguments from an argumentation framework, there is a lack
of justification behind their acceptability based on implicit argument
preferences. Preference-based argumentation frameworks allow one to determine
what arguments are justified given a set of preferences. Our research considers
the inverse of the standard reasoning problem, i.e., given an abstract
argumentation framework and a set of justified arguments, we compute what the
possible preferences over arguments are. Furthermore, there is a need to verify
(i.e., assess) that the computed preferences would lead to the acceptable sets
of arguments. This paper presents a novel approach and algorithm for
exhaustively computing and enumerating all possible sets of preferences
(restricted to three identified cases) for a conflict-free set of arguments in
an abstract argumentation framework. We prove the soundness, completeness and
termination of the algorithm. The research establishes that preferences are
determined using an extension-based approach after the evaluation phase
(acceptability of arguments) rather than stated beforehand. In this work, we
focus our research study on grounded, preferred and stable semantics. We show
that the complexity of computing sets of preferences is exponential in the
number of arguments, and thus, describe an approximate approach and algorithm
to compute the preferences. Furthermore, we present novel algorithms for
verifying (i.e., assessing) the computed preferences. We provide details of the
implementation of the algorithms (source code has been made available), various
experiments performed to evaluate the algorithms and the analysis of the
results.

我们提出了一种基于扩展的方法来计算和验证抽象论证系统中的偏好。我们的研究考虑了标准推理问题的逆，即在给定一个抽象论证框架和一组被证明的论证时，计算关于论证的所有可能偏好的方法和算法。我们证明了算法的正当性、完备性和终止性。该研究表明，偏好是在评估阶段（论证的可接受性）之后使用基于扩展的方法确定的，而不是事先声明的。我们的研究集中在基于地面、首选和稳定的语义上，我们发现计算偏好集的复杂度与论证数量呈指数关系，因此描述了一种近似方法和算法来计算偏好，并提供了验证所计算偏好的新算法。我们提供了算法的实施细节（源代码已提供）、用于评估算法的各种实验以及结果的分析。

基于扩展的抽象论证中首选项计算与验证方法

An Extension-based Approach for Computing and Verifying Preferences in  Abstract Argumentation

In this paper, we address the problem of change in an abstract argumentation
system. We focus on a particular change: the addition of a new argument which
interacts with previous arguments. We study the impact of such an addition on
the outcome of the argumentation system, more particularly on the set of its
extensions. Several properties for this change operation are defined by
comparing the new set of extensions to the initial one, these properties are
called structural when the comparisons are based on set-cardinality or
set-inclusion relations. Several other properties are proposed where
comparisons are based on the status of some particular arguments: the accepted
arguments; these properties refer to the evolution of this status during the
change, e.g., Monotony and Priority to Recency. All these properties may be
more or less desirable according to specific applications. They are studied
under two particular semantics: the grounded and preferred semantics.

本文研究了抽象论证系统中一种特定的添加新论点的变化，探讨了这种变化对于该论证系统中扩展集合的影响，基于集合基数和包含关系定义了几个结构属性，还提出了一些基于特定论点状态变化的属性，研究了这些属性在两种特定语义下的可行性和优越性。