This book aims to fill this gap, reviewing and describing major threads in the mathematical modeling of science dynamics for a wider academic and professional audience. The model classes presented here cover stochastic and statistical models, game-theoretic approaches, agent-based simulations, population-dynamics models, and complex network models. The book starts with a foundational chapter that defines and operationalizes terminology used in the study of science, and a review chapter that discusses the history of mathematical approaches to modeling science from an algorithmic-historiography perspective. It concludes with a survey of future challenges for science modeling and discusses their relevance for science policy and science policy studies.
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"The book is a comprehensive review of the mathematical models of science from its origins. ... each chapter has 'checkpoints', i.e., a box or a table presenting either a list of relevant questions together with short answers or a summary of the key-points discussed. This particular structure makes the book especially suited for graduate students and scholars ... . experts will surely appreciate the richness and depth of the cited literature, for the first time so well organized into a single book." (Stefano Balietti, Journal of Artificial Societies and Social Simulation, Vol. 15 (3), 2012)