On the Learning Behavior of Stochastic Automata Under a Nonstationary Random Environment

Abstract
We propose a new nonstationary random environment R(C1(t,ω),...,Cr(t,ω)), where t represents time and ω ∈ Ω, Ω being the supporting set of a probability measure space (Ω,B,μ). Moreover, the learning performance of the Lr-1 scheme under R(C1(t,ω),..., Cr(t,ω)) is discussed.

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