Browsing by Autor "Julio Waissman"

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    Fuzzy wavelet network with reinforcement learning: Application on underactuated system
    (2012) Iván S. Razo-Zapata; Luis Enrique Ramos‐Velasco; Julio C. Ramos Fernández; María Angélica Espejel-Rivera; Julio Waissman
    This paper presents a novel approach of reinforcement learning for continuous systems. The scheme is based in wavelet networks to approximating the continuous space of states. The structure of the wavelet network is dynamically generated accord to the explored regions and trained with a modified Q-Learning algorithm. The wavelet network include a fuzzy inference system which computes the value of the set of possible actions, in order to deal with continuous actions. This novel approach is called adaptive wavelet reinforcement learning control (AWRLC). Simulations of applying the proposed method to underactuated systems are performed to demonstrate the properties of the adaptive wavelet network controller.
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    Type-2 Neuro-Fuzzy Modeling for a Batch Biotechnological Process
    (Springer Science+Business Media, 2011) Pablo Hernández Torres; María Angélica Espejel Rivera; Luis Enrique Ramos‐Velasco; Julio C. Ramos Fernández; Julio Waissman