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Part I Foundations.- An Introduction to Modeling Science: Basic Model Types, Key Definitions, and a General Framework for the Comparison of Process Models.- Mathematical Approaches to Modeling Science From an Algorithmic-historiography Perspectice.- Part II Exemplary Model Type.- Knowledge Epidemics and Population Dynamics Models for Describing Idea Diffusion.- Agent-based Models of Science.- Evolutionary Game Theory and Complex Networks of Scientific Information.- Part III Exemplary Model Applications.- Dynamic Scientific Co-authorship Networks.- Citation Networks.- Part IV Outlook.- Science Policy and the Challenges for Modeling Science.- Index.
From the reviews: "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)