Seyed Hossein Khasteh

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In this paper, a new reinforcement learning approach is proposed which is based on a powerful concept named Active Learning Method (ALM) in model-ing. ALM expresses any multi-input-single-output system as a fuzzy combination of some single-input-single-output systems. The proposed method is an actor-critic system similar to Generalized Approximate Reasoning(More)
Active Learning Method (ALM) is a soft computing method which is used for modeling and control, based on fuzzy logic. Although ALM has shown that it acts well in dynamic environments, its operators cannot support it very well in complex situations due to losing data. Thus ALM can find better membership functions if more appropriate operators be chosen for(More)
Active Learning Method (ALM) is a soft computing method used for modeling and control based on fuzzy logic. All operators defined for fuzzy sets must serve as either fuzzy S-norm or fuzzy T-norm. Despite being a powerful modeling method, ALM does not possess operators which serve as S-norms and T-norms which deprive it of a profound analytical(More)
An effective approach for energy conservation in wireless sensor networks is scheduling sleep intervals for extraneous nodes while the remaining nodes stay active to provide continuous service. For the sensor network to operate successfully the active nodes must maintain both sensing coverage and network connectivity, It proved before if the communication(More)
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