Preface for the First International Workshop on Logical
                         Foundations of Neuro-Symbolic AI (LNSAI 2024)
                         Gianluca Cima1,* , Marco Console1 , Víctor Gutiérrez-Basulto2 , Pascal Hitzler3 and
                         Maurizio Lenzerini1
                         1
                           Sapienza University of Rome
                         2
                           Cardiff University
                         3
                           Kansas State University


                                      Abstract
                                      This is the preface of the Proceedings of the First International Workshop on Logical Foundations of Neuro-
                                      Symbolic AI (LNSAI 2024), which took place on 05 August 2024 in Jeju Island (South Korea). The workshop was
                                      co-located with the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI 2024).




                         Workshop Description: Deductive and Inductive Reasoning are the two pillars of Artificial In-
                         telligence (AI) systems that deal with data. Deductive Reasoning techniques are based on symbolic
                         manipulation of information and usually infer new knowledge using automated logic-based procedures.
                         On the contrary, Inductive Reasoning techniques learn patterns often using sub-symbolic representa-
                         tions such as Artificial Neural Networks. Using these representations, the former can derive accurate
                         and explainable knowledge but are susceptible to noisy data, whereas the latter are robust to data
                         diversity but generate predictions that can be potentially imprecise and generally opaque. Due to
                         these characteristics, deductive and inductive reasoning techniques excel at solving and struggle with
                         completely different, and often complementary, families of problems.
                            As a result, we are currently experiencing a new era of AI where symbolic and neural techniques
                         are being combined to leverage the best from both of them. It is therefore extremely important that
                         such promising synergy is accurately formalized at its core, and more specifically grounded on formal
                         methods, based on some form of logic. This workshop aims to strengthen the integration between
                         neural and symbolic approaches, with the goal of discussing methods and approaches for formalizing it.

                         General Chairs:

                                • Gianluca Cima (Sapienza University of Rome)
                                • Marco Console (Sapienza University of Rome)
                                • Víctor Gutiérrez-Basulto (Cardiff University)
                                • Pascal Hitzler (Kansas State University)
                                • Maurizio Lenzerini (Sapienza University of Rome)

                         Program Committee:

                                • Pablo Barceló (IMC, PUC Chile & IMFD Chile & CENIA)
                                • Steven Schockaert (Cardiff University)
                                • Floris Geerts (University of Antwerp)
                                • Yazmín Ibáñez-García (Cardiff University)
                          LNSAI 2024: First International Workshop on Logical Foundations of Neuro-Symbolic AI, August 05, 2024, Jeju, South Korea
                         *
                           Corresponding Editor.
                          $ cima@diag.uniroma1.it (G. Cima); console@diag.uniroma1.it (M. Console); gutierrezbasultov@cardiff.ac.uk
                          (V. Gutiérrez-Basulto); hitzler@k-state.edu (P. Hitzler); lenzerini@diag.uniroma1.it (M. Lenzerini)
                           0000-0003-1783-5605 (G. Cima); 0009-0004-5526-019X (M. Console); 0000-0002-6117-5459 (V. Gutiérrez-Basulto);
                          0000-0001-6192-3472 (P. Hitzler); 0000-0003-2875-6187 (M. Lenzerini)
                                     © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).


CEUR
                  ceur-ws.org
Workshop      ISSN 1613-0073
Proceedings
    • Raghava Mutharaju (University of Kentucky)
    • Frank van Harmelen (Vrije Universiteit Amsterdam)
    • Antonella Poggi (Sapienza University of Rome)
    • Luis Lamb (UFRGS, Federal University of Rio Grande do Sul)
    • Egor V. Kostylev (University of Oslo)
    • Alessandro Daniele (Fondazione Bruno Kessler)
    • Fabrizio Silvestri (Sapienza University of Rome)
    • Alessandro Ronca (University of Oxford)
    • Leilani H. Gilpin (UC Santa Cruz)
    • Abhilekha Dalal (Kansas State University)

Technical Program: The workshop received 14 submissions for peer review and only one was
rejected. In addition to the 13 presentations made as part of the workshop, we also had a presentation
by Efi Tsamoura (Samsung AI) as an invited speaker.
   Of the 13 papers accepted for presentation, the authors of the following six papers agreed to include
their paper in the workshop proceedings:

    • Abductive Symbolic Solver on Abstraction and Reasoning Corpus
    • Investigating Symbolic Capabilities of Large Language Models
    • Neuro-Symbolic AI in 2024: A Systematic Review
    • Formal Verification of Parameterised Neural-symbolic Multi-agent Systems (Extended Abstract)
    • On The Expressivity of Recurrent Neural Cascades (Extended Abstract)
    • What makes Models Compositional A Neuro-Symbolic Theoretical View (Extended Abstract)


Acknowledgments
This workshop has been supported by MUR under the PNRR project FAIR (PE0000013) and by the EU
under the H2020-EU.2.1.1 project TAILOR (grant id. 952215).