Speaker: Yi Wang (Professor, Department of Philosophy, Sun Yat-sen University (Zhuhai))

Moderator: Liying Zhang (Professor, Institute of Philosophy, University of Chinese Academy of Sciences)

Time: Friday, October 25, 2024, 14:00 - 16:00

Venue: Lecture Hall, Institute of Philosophy, Chinese Academy of Sciences (4th Floor, South Building, Building 4, Software Park, No. 4 Zhongguancun South Street, Haidian District, Beijing)

Organizer: Institute of Philosophy, Chinese Academy of Sciences

Abstract:
Similarity and dissimilarity measures are classic problems in data science. However, from a theoretical standpoint, research on similarity has lagged behind. This lecture will explore the theoretical properties of similarity from the perspective of epistemic logic. It will investigate how the concept of knowledge can be explained through similarity and how formal languages derived from this interpretation can characterize the conditions of similarity measures. Additionally, the talk will discuss the potential of similarity theory in frameworks such as probabilistic measures and fuzzy measures. Time permitting, the lecture will also introduce how similarity theory can enrich and advance epistemic logic and formal epistemology.

Speaker Bio:
Yi Wang is a Professor at the Department of Philosophy, Sun Yat-sen University (Zhuhai), and Head of the Logic Teaching and Research Section. He is also the Director of the Modern Logic Committee of the Chinese Association of Logic. His primary research interests lie in applied logic and philosophical logic, with a particular focus on modal logic theory and applications, logic of agents and multi-agent systems, and reasoning and representation in social networks.

 

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