A Self-Organizing Incremental Spatiotemporal Associative Memory Networks Model for Problems with Hidden State

Identifying the hidden state is important for solving problems with hidden state. We prove any deterministic partially observable Markov decision processes (POMDP) can be represented by a minimal, looping hidden state transition model and propose a heuristic state transition model constructing algor...

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Detalles Bibliográficos
Autor principal: Wang, Zuo-wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5112352/
https://www.ncbi.nlm.nih.gov/pubmed/27891146
http://dx.doi.org/10.1155/2016/7158507

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5112352/
https://www.ncbi.nlm.nih.gov/pubmed/27891146
http://dx.doi.org/10.1155/2016/7158507

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