コンピューティング科学研究領域のRACHARAK, Teeradaj講師が、タイ国立研究評議会(NRCT)より、National Research Award 2024の論文賞を受賞しました。

　NRCTは、科学の発展や社会科学的研究に貢献し、国民に恩恵をもたらすタイの研究者を支援し、その功績を称えています。2月2日から6日にかけてタイ（バンコク）にて開催された権威あるイベント「タイ発明家デー2024」にて、2024年度の栄誉あるNRCT国家研究賞の各受賞者の授賞式が行われ、タイ王室のMaha Chakri Sirindhorn王女殿下とNRCTから表彰状が授与されました。同賞には、国家優秀研究者賞、研究賞、発明賞、論文賞などが含まれ、合計170を超える賞が贈られました。
　RACHARAK講師は、タイのタマサート大学シリントーン国際工科大学博士課程在学中に、Nguyen Duy Hung助教授の指導のもと発表した学位論文が評価され、この度の受賞となりました。

■受賞年月日
　令和6年2月2日

■研究題目
　Structured Analogical Argumentation: Frameworks and Algorithms

■研究者、著者
　Racharak, Teeradaj

■受賞対象となった研究の内容
Analogical reasoning is a complex process based on a comparison between two pairs of concepts and states of affairs (aka. the source and the target) for characterizing certain features from one to another. Arguments which employ this process to support their claims are called analogical arguments. Our goals are to study the structure and the computation for their defeasibility in light of the argumentation theory. We outline the results of our study as comprising two parts in the following.

First, analogical reasoning involves in understanding the notion of similarity. To address this problem, we first take a look into the literature of similarity models. The most basic (but useful) one was introduced by (Tversky, 1977). In Tversky's model, an object is considered as a set of features. Then, the similarity of two objects is measured by the relationship between a number of common features and a number of different features. Nonetheless, not every feature needs to be cited in analogical arguments, the studies in (Hesse, 1965; Waller, 2001; Weinreb, 2016) reported that features used by the comparison should be 'relevant' for characterizing certain features from one to another. As part of the study, we formally investigate the characteristics of a 'similarity notion' for analogical arguments in this dissertation. Though our similarity models are posed in a general structure, our running examples are shown regarding the description logic formalism.

Second, analogical reasoning involves in understanding the structure of analogical arguments and computing their nature of defeasibility. These problems are indeed related to the study of structured argumentation and the acceptability of analogical arguments. As their results, we formally introduce a general framework in structured argumentation called assumption-based argumentation with predicate similarity ABA^(p) framework. This framework can be seen as an extension of assumption-based argumentation framework (ABA), in which not only assumptions can be used but also similarity of predicates (w.r.t. by the proposed similarity notion) are used to support a claim. ABA^(p) labels each argument tree with an analogical degree and different ways to aggregate numerical values are studied toward gullible/skeptical characteristics in agent reasoning. The acceptability of analogical arguments is evaluated w.r.t. Dung-styled semantics.

Finally, we demonstrate how our study can benefit the area of service science. Realistic examples are analyzed and a diverse range of applications is discussed.

■受賞にあたって一言
It is a great honor for me to receive the awards from Her Royal Highness Princess Maha Chakri Sirindhorn of Thailand and the National Research Council. The bestowed award certificates and award plate give me a great motivation to do better research that can benefit the public in future.

タイのMaha Chakri Sirindhorn女王殿下から授与された賞状

タイ国立研究評議会から授与された賞状

令和6年3月19日