asymptotic behavior learning automata operating in state dependent nonstationary environments

سال انتشار: 1383
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,602

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شناسه ملی سند علمی:

ACCSI10_035

تاریخ نمایه سازی: 25 آذر 1390

چکیده مقاله:

in this paper we intorduce a new state dependent nonstationary environment and study the asymptotic behavior of SLrI learning algorithm operating under the proposed environment it is shown that the SLR-I automaton operating in the proposed nontationary environment equalizes the expected penalty strengths of actions this model was motivated by applications of learning automata in call admission in cellular networks

نویسندگان

hamid beigy

computer engineering department sharif university of technology

m.r meybodi

soft computing laboratory computer engineering department amirkabir university of tech