Learning Automata Approach for Social Networks

丛 书 名：Studies in Computational Intelligence

版本说明：1st ed. 2019

作     者：Alireza Rezvanian Behnaz Moradabadi Mina Ghavipour Mohammad Mehdi Daliri Khomami Mohammad Reza Meybodi 

I S B N：(纸本) 9783030107666 

出 版 社：Springer International Publishing 

出 版 年：2019年

页      数：xvii, 329 pages页

主 题 词：Computational Intelligence. Artificial Intelligence. Social Media. 

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

摘      要：This book begins by briefly explaining learning automata (LA) models and a recently developed cellular learning automaton (CLA) named wavefront CLA. Analyzing social networks is increasingly important, so as to identify behavioral patterns in interactions among individuals and in the networks evolution, and to develop the algorithms required for meaningful analysis. As an emerging artificial intelligence research area, learning automata (LA) has already had a significant impact in many areas of social networks. Here, the research areas related to learning and social networks are addressed from bibliometric and network analysis perspectives. In turn, the second part of the book highlights a range of LA-based applications addressing social network problems, from network sampling, community detection, link prediction, and trust management, to recommender systems and finally influence maximization. Given its scope, the book offers a valuable guide for all researchers whose work involves reinforcement learning, social networks and/or artificial intelligence.