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Assuming that agents are equipped with some individual revision machinery, our concern will be to investigate how (under what conditions) convergence to a consistent state can be guaranteed at more global levels: (i) between two agents; (ii) in a clique of agents; and (iii) in general in a connected society of agents.
Under mild regularity conditions, convergence to a local optimum is guaranteed if one uses an appropriate schedule for decreasing η towards 0 during learning [21].
Various studies have shown that under certain conditions convergence is guaranteed to a stable equilibrium point [ 51].
Similar(57)
The conditions of convergence of the prediction error are investigated through a LMI based design.
Furthermore, necessary and sufficient conditions for convergence to a given infinitely divisible distribution are found.
The voltage temperature coefficient of the PV module is included in the boundary conditions for convergence stability.
We also provide conditions for convergence of the state estimation error and for ℒ2 and ℒ∞ input-to-state stability.
Remark 2.3 (Approximating initial conditions for convergence).
In controlling suitable conditions, strong convergence theorems are proven.
Under reasonable conditions, strong convergence theorems are proven.
Compactness is one of the main conditions for convergence.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com