Comparison of SAT-based and ASP-based Algorithms for Inconsistency Measurement

要約

命題知識ベースにおける矛盾度決定問題を解くための、充足可能性問題(SAT)解法と解答集合計画法(ASP)に基づくアルゴリズムを提案する。我々は、それぞれの決定問題が多項式階層の第1レベルにある6つの異なる矛盾尺度を考察する。すなわち、contension inconsistency measure、forgoting-based inconsistency measure、hitting set inconsistency measure、max-distance inconsistency measure、sum-distance inconsistency measure、hit-distance inconsistency measureである。広範な実験的分析において、SATベースとASPベースのアプローチを互いに比較し、また素朴なベースラインアルゴリズムとも比較した。その結果、全体として、SATベースとASPベースの両アプローチは、実行時間の点で明らかに素朴なベースライン法を上回ることが示された。さらに、提案したASPベースのアプローチは、本研究で考慮した6つの不整合性指標全てに関して、SATベースのアプローチよりも優れた性能を示す。さらに、前述の結果をより詳細に説明するために、追加の実験を行う。

要約(オリジナル)

We present algorithms based on satisfiability problem (SAT) solving, as well as answer set programming (ASP), for solving the problem of determining inconsistency degrees in propositional knowledge bases. We consider six different inconsistency measures whose respective decision problems lie on the first level of the polynomial hierarchy. Namely, these are the contension inconsistency measure, the forgetting-based inconsistency measure, the hitting set inconsistency measure, the max-distance inconsistency measure, the sum-distance inconsistency measure, and the hit-distance inconsistency measure. In an extensive experimental analysis, we compare the SAT-based and ASP-based approaches with each other, as well as with a set of naive baseline algorithms. Our results demonstrate that overall, both the SAT-based and the ASP-based approaches clearly outperform the naive baseline methods in terms of runtime. The results further show that the proposed ASP-based approaches perform superior to the SAT-based ones with regard to all six inconsistency measures considered in this work. Moreover, we conduct additional experiments to explain the aforementioned results in greater detail.

arxiv情報

提供元, 利用サービス

arxiv.jp, DeepL