Rino Falcone, Cristiano Castelfranchi, Alessandro Sapienza, Filippo Cantucci (eds.)
WOA 2023 – 24th Workshop “From Objects to Agents”, pages 232–245
CEUR Workshop Proceedings (AIxIA Series) 3579
Sun SITE Central Europe, RWTH Aachen University
November 2023
In the realm of cognitive agents, including both human users and AI systems, explainable clustering algorithms have gained prominence. These algorithms offer enhanced transparency, making clustering results comprehensible to users and aiding AI systems in decision-making. They also facilitate knowledge discovery by revealing cluster characteristics, reducing cognitive load for users, and playing a vital role in ethical and bias mitigation. This paper introduces an innovative extension of the existing PSyKE framework, designed to support explainable clustering techniques and, thus, to augment cognitive agent capabilities. State-of-the-art review, experiment findings, and a synthesis of key insights are also provided.
keywords
Explainable clustering, Explainable artificial intelligence, Symbolic knowledge extraction, PSyKE
reference talk
origin event
journal or series
funding project
AEQUITAS — Assessment and Engineering of eQuitable, Unbiased, Impartial and Trustworthy Ai Systems
(01/11/2022–31/10/2025)
TAILOR — Foundations of Trustworthy AI – Integrating Reasoning, Learning and Optimization
(01/09/2020–31/08/2024)
works as
reference publication for talk
Unlocking Insights and Trust: The Value of Explainable Clustering Algorithms for Cognitive Agents (WOA 2023, 08/11/2023) — Giovanni Ciatto (Federico Sabbatini, Roberta Calegari)
CEUR Workshop Proceedings (CEUR-WS.org)