---
res:
  bibo_abstract:
  - Explainable artificial intelligence (XAI) is essential for critical domains such
    as healthcare and autonomous systems to build trust and confidence in real-world
    deployment. In this context, description logic knowledge bases (KBs) provide structured
    and semantically rich representations that support reasoning and informed decision-making.
    A core task in applying KBs to XAI is class expression learning (CEL), which generates
    explainable logical descriptions for classifying instances within KBs. Unlike
    black-box models with opaque internal mechanisms, CEL provides global explainability
    and ease of integration with domain knowledge. However, current approaches to
    CEL face significant limitations such as poor scalability, failure to capture
    rare patterns, and limited exploration of the vast class expression search space.
    To overcome these limitations, we introduce LYRA, a novel multi-agent deep reinforcement
    learning framework that formulates CEL as a collaborative planning task under
    uncertainty. The integration of the Dempster–Shafer theory enables agents to effectively
    reason under ambiguity and manage conflicting or inconsistent information. Our
    experiments show that LYRA outperforms state-of-the-art methods on seven out of
    eight datasets, demonstrating robust and scalable CEL. Additionally, LYRA offers
    interpretable decisions and employs advanced search strategies, enabling the discovery
    of more precise and expressive class expressions than existing approaches.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Amgad
      foaf_name: Abdulmaqsod, Amgad
      foaf_surname: Abdulmaqsod
  - foaf_Person:
      foaf_givenName: Yasir
      foaf_name: Mahmood, Yasir
      foaf_surname: Mahmood
  - foaf_Person:
      foaf_givenName: Axel-Cyrille
      foaf_name: Ngonga Ngomo, Axel-Cyrille
      foaf_surname: Ngonga Ngomo
  - foaf_Person:
      foaf_givenName: Mohamed Ahmed
      foaf_name: Sherif, Mohamed Ahmed
      foaf_surname: Sherif
  dct_date: 2026^xs_gYear
  dct_subject:
  - amgad dice enexa fairomics mahmood ngonga sailproject sherif simba whale
  dct_title: 'LYRA: Belief-Driven Scalable Class Expression Learning in Description
    Logics@'
...