NeSy 2023

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Special Track on Neuro-symbolic xAI at the 1st World Conference on eXplainable Artificial Intelligence
Lisbon, Portugal, 26/07/2023–28/07/2023

Integrating symbolic and sub-symbolic approaches to make intelligent systems understandable and explainable is at the core of new fields such as neuro-symbolic computing. Neural-symbolic computing aims to integrate two fundamental cognitive abilities: learning from the environment and reasoning from what has been learned. Neural-symbolic computing reconciles the advantages of robust learning in neural networks and reasoning and interpretability of symbolic representation, enabling explainability via symbolic representations for network models.

topics of interest
  • Probabilistic methods for explainability with Neural Networks
  • Enabling explanations with Computing Logic Programs with Neural Networks
  • Learning Logic Programs for explainable AI systems
  • Enabling explanations with Neurosymbolic Logic Programming
  • Enabling explanations with Nonmonotonic Reasoning and Learning
  • Machine Learning for Theorem Proving
  • Abductive Logic Programming and Learning for XAI
  • Learning Answer Set Programs for XAI
  • Interpretability and Explainability via symbolic knowledge extraction and injection from/to opaque models
  • Enabling explanations with Inductive logic programming
  • Explainable planning
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