Different algorithms categorized in reinforcement learning












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(Originally asked at cross validated forum: https://stats.stackexchange.com/questions/401615/different-algorithms-categorized-in-reinforcement-learning)



For some time I am going through reinforcement learning, and have found a lot of diverse information specially in area of Policies (algorithms).



I figured out that policies can be classified in On Vs Off, Model based vs Model Free, Also, these are kind of Q, DQN, SARSA etc.



I am looking for a categorized table where these are all well categorized . There is a good table given in wikipedia, but I think it is incomplete (Wikipedia page url - Reinforcement learning ), as it does not list Model based algorithms and it does not list examples where one kind of algorithm is a best fit.



Can someone help getting a bird's eye view of all, current known, reinforcement policies/algorithms, categorized in tabular format, and where to apply which one (and where not).










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    0












    $begingroup$


    (Originally asked at cross validated forum: https://stats.stackexchange.com/questions/401615/different-algorithms-categorized-in-reinforcement-learning)



    For some time I am going through reinforcement learning, and have found a lot of diverse information specially in area of Policies (algorithms).



    I figured out that policies can be classified in On Vs Off, Model based vs Model Free, Also, these are kind of Q, DQN, SARSA etc.



    I am looking for a categorized table where these are all well categorized . There is a good table given in wikipedia, but I think it is incomplete (Wikipedia page url - Reinforcement learning ), as it does not list Model based algorithms and it does not list examples where one kind of algorithm is a best fit.



    Can someone help getting a bird's eye view of all, current known, reinforcement policies/algorithms, categorized in tabular format, and where to apply which one (and where not).










    share|improve this question









    $endgroup$















      0












      0








      0





      $begingroup$


      (Originally asked at cross validated forum: https://stats.stackexchange.com/questions/401615/different-algorithms-categorized-in-reinforcement-learning)



      For some time I am going through reinforcement learning, and have found a lot of diverse information specially in area of Policies (algorithms).



      I figured out that policies can be classified in On Vs Off, Model based vs Model Free, Also, these are kind of Q, DQN, SARSA etc.



      I am looking for a categorized table where these are all well categorized . There is a good table given in wikipedia, but I think it is incomplete (Wikipedia page url - Reinforcement learning ), as it does not list Model based algorithms and it does not list examples where one kind of algorithm is a best fit.



      Can someone help getting a bird's eye view of all, current known, reinforcement policies/algorithms, categorized in tabular format, and where to apply which one (and where not).










      share|improve this question









      $endgroup$




      (Originally asked at cross validated forum: https://stats.stackexchange.com/questions/401615/different-algorithms-categorized-in-reinforcement-learning)



      For some time I am going through reinforcement learning, and have found a lot of diverse information specially in area of Policies (algorithms).



      I figured out that policies can be classified in On Vs Off, Model based vs Model Free, Also, these are kind of Q, DQN, SARSA etc.



      I am looking for a categorized table where these are all well categorized . There is a good table given in wikipedia, but I think it is incomplete (Wikipedia page url - Reinforcement learning ), as it does not list Model based algorithms and it does not list examples where one kind of algorithm is a best fit.



      Can someone help getting a bird's eye view of all, current known, reinforcement policies/algorithms, categorized in tabular format, and where to apply which one (and where not).







      reinforcement-learning q-learning






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      share|improve this question










      asked 9 hours ago









      Sandeep BSandeep B

      1067




      1067






















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