Adaptive Learning Algorithms and Platforms: A Concise Overview

2022 ◽  
pp. 3-12
Author(s):  
Hammadi Mezin ◽  
Saad Yasser Kharrou ◽  
Ayoub Ait Lahcen
Keyword(s):  
Adaptive Learning ◽  
Learning Algorithms ◽  
Concise Overview

scholarly journals Adaptive Learning Algorithms for Traffic Games with Naive Users

2013 ◽  
Vol 80 ◽  
pp. 806-817 ◽  
Author(s):  
Toshihiko Miyagi ◽  
Genaro Peque ◽  
Junya Fukumoto
Keyword(s):  
Adaptive Learning ◽  
Learning Algorithms

Novel On-Line Adaptive Learning Algorithms for Blind Deconvolution Using the Natural Gradient Approach

1997 ◽  
Vol 30 (11) ◽  
pp. 1007-1012 ◽  
Author(s):  
Shun-ichi Amari ◽  
Scott C. Douglas ◽  
Andrzej Cichocki ◽  
Howard H. Yang
Keyword(s):  
Adaptive Learning ◽  
Blind Deconvolution ◽  
Learning Algorithms ◽  
Natural Gradient ◽  
On Line ◽  
Gradient Approach

Stochastic Learning of Strategic Equilibria for Auctions

1999 ◽  
Vol 11 (5) ◽  
pp. 1199-1209
Author(s):  
Samy Bengio ◽  
Yoshua Bengio ◽  
Jacques Robert ◽  
Gilles Bélanger
Keyword(s):  
Neural Networks ◽  
Adaptive Learning ◽  
Decision Model ◽  
Learning Algorithms ◽  
Space Versus ◽  
Action Space ◽  
Moving Target ◽  
Stochastic Learning ◽  
Strategic Equilibria

This article presents a new application of stochastic adaptive learning algorithms to the computation of strategic equilibria in auctions. The proposed approach addresses the problems of tracking a moving target and balancing exploration (of action space) versus exploitation (of better modeled regions of action space). Neural networks are used to represent a stochastic decision model for each bidder. Experiments confirm the correctness and usefulness of the approach.

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