Collective learning modeling based on the kinetic theory of active particles

被引:83
|
作者
Burini, D. [1 ,2 ]
De Lillo, S. [1 ,2 ]
Gibelli, L. [3 ]
机构
[1] Univ Perugia, Dept Math & Comp Sci, Via Vanvitelli 1, I-06123 Perugia, Italy
[2] Ist Nazl Fis Nucl, Sez Perugia, Perugia, Italy
[3] Politecn Torino, Dept Math Sci, Corso Duca Abruzzi 24, I-10129 Turin, Italy
关键词
Kinetic theory; Active particles; Stochastic differential games; Social learning; Monte Carlo particle method; MOTIVATION LOSSES; DYNAMICS; SYSTEMS; EVOLUTION; CANCER;
D O I
10.1016/j.plrev.2015.10.008
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:123 / 139
页数:17
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