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Neural-Symbolic Learning and Reasoning [electronic resource] : 18th International Conference, NeSy 2024, Barcelona, Spain, September 9–12, 2024, Proceedings, Part II / edited by Tarek R. Besold, Artur d’Avila Garcez, Ernesto Jimenez-Ruiz, Roberto Confalonieri, Pranava Madhyastha, Benedikt Wagner.

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TextSeries: Lecture Notes in Artificial Intelligence ; 14980Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XXIII, 341 p. 93 illus., 74 illus. in color. online resourceContent type:

text

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computer

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online resource

ISBN:

9783031711701

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Additional physical formats: Printed edition:: No title; Printed edition:: No titleLOC classification:

QA76.758

Online resources:

Resursa online

Contents:

-- NeSy 2024 Papers. -- NeSy 2024 XAI Special Track. -- NeSy 2024 GenAI Special Track.

In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024, held in Barcelona, Spain during September 9-12th, 2024. The 30 full papers and 18 short papers were carefully reviewed and selected from 89 submissions, which presented the latest and ongoing research work on neurosymbolic AI. Neurosymbolic AI aims to build rich computational models and systems by combining neural and symbolic learning and reasoning paradigms. This combination hopes to form synergies among their strengths while overcoming their complementary weaknesses.

Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)

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-- NeSy 2024 Papers. -- NeSy 2024 XAI Special Track. -- NeSy 2024 GenAI Special Track.

This book constitutes the refereed proceedings of the 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024, held in Barcelona, Spain during September 9-12th, 2024. The 30 full papers and 18 short papers were carefully reviewed and selected from 89 submissions, which presented the latest and ongoing research work on neurosymbolic AI. Neurosymbolic AI aims to build rich computational models and systems by combining neural and symbolic learning and reasoning paradigms. This combination hopes to form synergies among their strengths while overcoming their complementary weaknesses.

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