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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.
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