Sentence examples for stochastic learning from inspiring English sources

Generally, there are three learning process types: individual learning, joint-action learning, and stochastic learning.

Stochastic learning automata have previously been shown to have global optimisation properties making them suitable for the optimisation of filter coefficients.

Based on the concept of learning automata, we propose a distributed stochastic learning algorithm to adaptively update the bidding strategies of the secondary users and the auction mechanism of the primary user in a non-cooperative manner.

A reconfigurable multi-hop wireless network is studied by Shiang and van der Schaar [62], wherein a decentralized stochastic learning process optimizes the transmission decisions of nodes aimed at supporting mission-critical applications.

A distributed and interconnected stochastic learning automata system is implemented to manage, in a unified and unique way, the reactive power in complex power grids with stochastic reactive power demand and detect the vulnerable part.

can generate different predictions since they involve stochastic learning.

The aim of this study is to present and discuss the property of a stochastic reinforcement learning based model of upper limb posture generation that exhibits both properties.

We consider a two-period supply chain where the supplier with stochastic cost learning sells products through a retailer who may keep market potential information private.

With sample average approximation method, we propose stochastic distributed learning algorithms to help secondary users satisfy the constraints with the feedback information from primary links when maximizing the utilities.

Specifically this paper shows how to design stochastic iterative learning control systems such that the networked-system with a repetitive task is robust stable against measurement and process noises and independent, intermittent output channel dropouts.

Particularly, a new stochastic mini-batch learning algorithm is proposed to train a Mahalanobis self-organising map (MSOM) model.