@article{wangAdaptiveDynamicProgramming2009,
  title = {Adaptive Dynamic Programming: An Introduction},
  author = {Wang, Fei-Yue and Zhang, Huaguang and Liu, Derong},
  date = {2009-05},
  journaltitle = {Computational Intelligence Magazine, IEEE},
  volume = {4},
  pages = {39--47},
  issn = {1556-603X},
  doi = {10.1109/mci.2009.932261},
  url = {https://doi.org/10.1109/mci.2009.932261},
  abstract = {In this article, we introduce some recent research trends within the field of adaptive/approximate dynamic programming (ADP), including the variations on the structure of ADP schemes, the development of ADP algorithms and applications of ADP schemes. For ADP algorithms, the point of focus is that iterative algorithms of ADP can be sorted into two classes: one class is the iterative algorithm with initial stable policy; the other is the one without the requirement of initial stable policy. It is generally believed that the latter one has less computation at the cost of missing the guarantee of system stability during iteration process. In addition, many recent papers have provided convergence analysis associated with the algorithms developed. Furthermore, we point out some topics for future studies.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-12017332,adaptive-control,approximate-dynamic-programming,control-problem,neuro-dynamic-programming},
  number = {2}
}

{"_id":"CJE3bHL6NaJLJaBPe","bibbaseid":"wang-zhang-liu-adaptivedynamicprogramminganintroduction","authorIDs":[],"author_short":["Wang, F.","Zhang, H.","Liu, D."],"bibdata":{"bibtype":"article","type":"article","title":"Adaptive Dynamic Programming: An Introduction","author":[{"propositions":[],"lastnames":["Wang"],"firstnames":["Fei-Yue"],"suffixes":[]},{"propositions":[],"lastnames":["Zhang"],"firstnames":["Huaguang"],"suffixes":[]},{"propositions":[],"lastnames":["Liu"],"firstnames":["Derong"],"suffixes":[]}],"date":"2009-05","journaltitle":"Computational Intelligence Magazine, IEEE","volume":"4","pages":"39–47","issn":"1556-603X","doi":"10.1109/mci.2009.932261","url":"https://doi.org/10.1109/mci.2009.932261","abstract":"In this article, we introduce some recent research trends within the field of adaptive/approximate dynamic programming (ADP), including the variations on the structure of ADP schemes, the development of ADP algorithms and applications of ADP schemes. For ADP algorithms, the point of focus is that iterative algorithms of ADP can be sorted into two classes: one class is the iterative algorithm with initial stable policy; the other is the one without the requirement of initial stable policy. It is generally believed that the latter one has less computation at the cost of missing the guarantee of system stability during iteration process. In addition, many recent papers have provided convergence analysis associated with the algorithms developed. Furthermore, we point out some topics for future studies.","keywords":"*imported-from-citeulike-INRMM,~INRMM-MiD:c-12017332,adaptive-control,approximate-dynamic-programming,control-problem,neuro-dynamic-programming","number":"2","bibtex":"@article{wangAdaptiveDynamicProgramming2009,\n title = {Adaptive Dynamic Programming: An Introduction},\n author = {Wang, Fei-Yue and Zhang, Huaguang and Liu, Derong},\n date = {2009-05},\n journaltitle = {Computational Intelligence Magazine, IEEE},\n volume = {4},\n pages = {39--47},\n issn = {1556-603X},\n doi = {10.1109/mci.2009.932261},\n url = {https://doi.org/10.1109/mci.2009.932261},\n abstract = {In this article, we introduce some recent research trends within the field of adaptive/approximate dynamic programming (ADP), including the variations on the structure of ADP schemes, the development of ADP algorithms and applications of ADP schemes. For ADP algorithms, the point of focus is that iterative algorithms of ADP can be sorted into two classes: one class is the iterative algorithm with initial stable policy; the other is the one without the requirement of initial stable policy. It is generally believed that the latter one has less computation at the cost of missing the guarantee of system stability during iteration process. In addition, many recent papers have provided convergence analysis associated with the algorithms developed. Furthermore, we point out some topics for future studies.},\n keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-12017332,adaptive-control,approximate-dynamic-programming,control-problem,neuro-dynamic-programming},\n number = {2}\n}\n\n","author_short":["Wang, F.","Zhang, H.","Liu, D."],"key":"wangAdaptiveDynamicProgramming2009","id":"wangAdaptiveDynamicProgramming2009","bibbaseid":"wang-zhang-liu-adaptivedynamicprogramminganintroduction","role":"author","urls":{"Paper":"https://doi.org/10.1109/mci.2009.932261"},"keyword":["*imported-from-citeulike-INRMM","~INRMM-MiD:c-12017332","adaptive-control","approximate-dynamic-programming","control-problem","neuro-dynamic-programming"],"downloads":0},"bibtype":"article","biburl":"https://tmpfiles.org/dl/58794/INRMM.bib","creationDate":"2020-07-02T22:41:33.016Z","downloads":0,"keywords":["*imported-from-citeulike-inrmm","~inrmm-mid:c-12017332","adaptive-control","approximate-dynamic-programming","control-problem","neuro-dynamic-programming"],"search_terms":["adaptive","dynamic","programming","introduction","wang","zhang","liu"],"title":"Adaptive Dynamic Programming: An Introduction","year":null,"dataSources":["DXuKbcZTirdigFKPF"]}