ANFIS + Reinforcement Learning

From: Vijay Patil (vcp0123@yahoo.com)
Date: Mon Oct 08 2001 - 15:11:37 MET DST

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    Hi,

    [1]"ANFIS: Adaptive Network Based FIS", Roger Jang,
    IEEE Trans. on Systems, Man and Cybernetics, Vol 23, No 3, 1993.
    [2] "Neuro Fuzzy and Soft Computing", Jang Sun Mizutani., Prentice
    Hall 1997.
     
    I am using ANFISEDIT in Fuzzy Logic Toolbox (MATLAB 5.2), and found it
    very useful for my research.
    I have written code in C++ with the help of reference [1]. It is
    working properly, but when I compared it with ANFISEDIT the error
    given by my code is more. As given in [1], I have used hybrid rule
    where steepest gradient is used in backward pass and LSE in forward
    pass.
    So why is my code is showing more error than your ANFISEDIT under same
    conditions.? What are the improvements that are needed in [1]?

    My project requires use GARIC architecture[Berenji an Khedkar], where
    desired output is not available but the reinforcement is available
    from Action Evaluation Network(AEN). On page no. 483 of [2] I found
    that ANFIS is similar to Action Selection Network(ASN) of GARIC, but
    the problem is, in that case, Hybrid Learning Rule can not be used as
    desired output is not available. As we know, steepest gradient method
    is slow and may get trapped in local minima. * This severely limits
    the use of Hybrid Learnig rule as far Reinforcement Learning is
    considered *. So what is the solution to improve the learnig in FIS
    when desired output is not available and reinforcemnt(penalty) is
    available?. Please provide me some information on this issue.
    Thanks. With Best Regards.

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