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Topic: logic

Unified directory of all items matching this research classification.
13 Linked Entries
Laboratory Members (3)
MJ

Milagros Jacinto

Estudiante de grado
#artificial intelligence
#explainable ai
#logic
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MM

Martin Moschettoni

Estudiante de posgrado
#artificial intelligence
#explainable ai
#logic
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Claudia avatar

Claudia Pons

Investigador
#software engineering
#artificial intelligence
#formal methods
#logic
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Research Projects (1)

Técnicas de Inteligencia Artificial Neuro-simbólica

Director: Claudia Pons
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Academic Theses (1)

Agregando polimorfismo a una lógica que identifica proposiciones isomorfas

Undergraduate | Student: Sottile, Cristian 2020
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Research Scholarships (1)

Técnicas de Inteligencia artificial basadas en una integración de la lógica simbólica y no-simbólica

Beca de entrenamiento | Student: Ariel Dapia Graziani
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Scientific Bibliography (7)

Pablo Negro and Claudia Pons (2024). “Rule Extraction in Trained Feedforward Deep Neural Networks: Integrating Cosine Similarity and Logic for Explainability”. International Journal of Artificial Intelligence and Machine Learning (IJAIML). ISSN: 2642-1577|EISSN: 2642-1585| https://doi.org/10.4018/IJAIML.347988 Volume 13, Issue 1, Article 2.

Pablo Negro and Claudia Pons (2024). “Rule Extraction in Trained Feedforward Deep Neural Networks: Integrating Cosine Similarity and Logic for Explainability”. International Journal of Artificial Intelligence and Machine Learning (IJAIML). ISSN: 2642-1577|EISSN: 2642-1585| https://doi.org/10.4018/IJAIML.347988 Volume 13, Issue 1, Article 2.
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Pablo Negro and Claudia Pons (2024). Extracting rules from trained feedforward neural networks with first order logic. Electronic Journal of SADIO (EJS), 23(1). pg.58-80. June 2024.https://doi.org/10.24215/15146774e040

Pablo Negro and Claudia Pons (2024). Extracting rules from trained feedforward neural networks with first order logic. Electronic Journal of SADIO (EJS), 23(1). pg.58-80. June 2024.https://doi.org/10.24215/15146774e040
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Artificial Intelligence techniques based on the integration of symbolic logic and deep neural networks: A systematic review of the literature

Negro, P., & Pons, C. (2022). Artificial Intelligence techniques based on the integration of symbolic logic and deep neural networks: A systematic review of the literature. Inteligencia Artificial, 25(69), 13–41. https://doi.org/10.4114/intartif.vol25iss69pp13-41
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The unity and identity of decidable objects and double-negation sheaves

Menni, M. (2018). The unity and identity of decidable objects and double-negation sheaves. The Journal of Symbolic Logic, 83(04), 1667–1679. https://doi.org/10.1017/jsl.2018.42
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Every Rig with a One-Variable Fixed Point Presentation is the Burnside Rig of a Prextensive Category

Menni, M. (2017). Every Rig with a One-Variable Fixed Point Presentation is the Burnside Rig of a Prextensive Category. Applied Categorical Structures, 25(4), 663–707. https://doi.org/10.1007/s10485-016-9475-6
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Claudia Pons, Ricardo Rosenfeld y Clara Smith. “Lógica para informática”. Editorial de la Universidad Nacional de La Plata (EDULP). ISBN: 978-950-34-1510-8. Ext.: 165 p. (2017). Disponible en repositorio SEDICI.

Claudia Pons, Ricardo Rosenfeld y Clara Smith. “Lógica para informática”. Editorial de la Universidad Nacional de La Plata (EDULP). ISBN: 978-950-34-1510-8. Ext.: 165 p. (2017). Disponible en repositorio SEDICI.
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A representation theorem for integral rigs and its applications to residuated lattices

Castiglioni, J. L., Menni, M., & Botero, W. J. Z. (2016). A representation theorem for integral rigs and its applications to residuated lattices. Journal of Pure and Applied Algebra, 220(10), 3533–3566. https://doi.org/10.1016/j.jpaa.2016.04.014
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