Fixed Point Theory Analysis of a Lambda Policy Iteration with Randomization for the ¿iri¿ Contraction Operator

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2025

Autores

Belhenniche, A (Autor) Outra; Chertovskih, R (Autor) FEUP

Ata de Conferência Internacional

Título: Lecture Notes in Electrical Engineering

Páginas: 94-105

16th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2024

Porto, 17 July 2024 through 19 July 2024

Indexação

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-018-NMP

DOI: 10.1007/978-3-031-81724-3_10

Abstract (EN): We apply methods of the fixed point theory to a Lambda policy iteration with a randomization algorithm for weak contractions mappings. This type of mappings covers a broader range than the strong contractions typically considered in the literature, such as ¿iri¿ contraction. Specifically, we explore the characteristics of reinforcement learning procedures developed for feedback control within the context of fixed point theory. Under relatively general assumptions, we identify the sufficient conditions for convergence with a probability of one in infinite-dimensional policy spaces. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11