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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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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Hindawi Publishing Corporation
2016
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| 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 |