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“Discrete models” refers to books about mathematical and computational models that describe systems in terms of distinct states, events, or time steps rather than continuous variables. Titles in this category typically cover foundations (combinatorics, graph theory, probability on countable spaces) and methods such as finite-state machines and automata, Markov chains and hidden Markov models, Bayesian networks, queueing systems, Petri nets, cellular and agent-based models, discrete-event simulation, graph and network models, and combinatorial and integer optimization. Emphasis is on algorithms, analysis, and implementation for systems that are inherently stepwise or countable, or are modeled discretely for tractability. Applications span computer science, operations research, logistics, telecommunications, epidemiology, economics, and network science, with books ranging from introductory texts to advanced research monographs and practical handbooks.

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