Graph representations for reinforcement learning

Graph analysis is becoming increasingly important due to the expressive power of graph models and the efficient algorithms available for processing them. Reinforcement Learning is one domain that could benefit from advancements in graph analysis, given that a learning agent may be integrated into an...

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Guardado en:
Detalles Bibliográficos
Autores principales: Schab, Esteban, Casanova, Carlos, Piccoli, Fabiana
Formato: Articulo
Lenguaje:Inglés
Publicado: 2024
Materias:
Ciencias Informáticas
Computational Intelligence
Reinforcement Learning
Graph Embeddings
unsupervised GRL
Whole Graph Embedding
Inteligencia Computacional
Aprendizaje por Refuerzo
Embeddings de grafos
GRL no supervisado
Embedding de grafo entero
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/166757
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata

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