Fitted Value Iteration
Fitted Value Iteration is a model-free reinforcement learning algorithm that approximates the value function by iteratively refining a parametric or non-parametric function fit to sampled Bellman backups, thereby enabling scalable and continuous-state policy evaluation.
19
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1.2K
Citations
53
Authors
34
Institutions
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2017–2026
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34

Supélec
Gif-sur-Yvette, France
3 h-index
5 publications
189 citations

Hungarian Academy of Sciences
Budapest, Hungary
2 h-index
3 publications
127 citations
University of Cambridge
Cambridge, United Kingdom
1 h-index
2 publications
224 citations
Centre de Mathématiques Appliquées de l'École polytechnique
Palaiseau, France
1 h-index
1 publications
67 citations
Orange (France)
Paris, France
1 h-index
2 publications
32 citations
Georgia Tech-CNRS Laboratory
Metz, France
1 h-index
1 publications
26 citations
Consejo Superior de Investigaciones Científicas
Madrid, Spain
1 h-index
2 publications
64 citations
Flemish Institute for Technological Research
Mol, Belgium
1 h-index
1 publications
339 citations
1–8 of 34
Repository · 2 publications · 48 citations
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JAIR · 1 publications · 34 citations
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1 publications · 339 citations
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Repository · 1 publications · 71 citations
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Repository · 1 publications · 12 citations
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