On the Lock-in Probability of Stochastic Approximation
Combinatorics, Probability and Computing
Stochastic Approximations and Differential Inclusions, Part II: Applications
Mathematics of Operations Research
A Stochastic Algorithm for Feature Selection in Pattern Recognition
The Journal of Machine Learning Research
Computational Economics
Near-Potential Games: Geometry and Dynamics
ACM Transactions on Economics and Computation - Special Issue on Algorithmic Game Theory
Broadcast control of multi-agent systems
Automatica (Journal of IFAC)
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It is known that some problems of almost sure convergence for stochastic approximation processes can be analyzed via an ordinary differential equation (ODE) obtained by suitable averaging. The goal of this paper is to show that the asymptotic behavior of such a process can be related to the asymptotic behavior of the ODE without any particular assumption concerning the dynamics of this ODE. The main results are as follows: a) The limit sets of trajectory solutions to the stochastic approximation recursion are, under classical assumptions, almost surely nonempty compact connected sets invariant under the flow of the ODE and contained in its set of chain-recurrence. b) If the gain parameter goes to zero at a suitable rate depending on the expansion rate of the ODE, any trajectory solution to the recursion is almost surely asymptotic to a forward trajectory solution to the ODE.