Leseprobe
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Agent-Based and Individual-Based Modeling
Volker Grimm, Steven F. Railsback
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Naturwissenschaften, Medizin, Informatik, Technik / ÷kologie
Beschreibung
The essential textbook on agent-based modeling—now fully updated and expanded
Agent-Based and Individual-Based Modeling has become the standard textbook on the subject for classroom use and self-instruction. Drawing on the latest version of NetLogo and fully updated with new examples, exercises, and an enhanced text for easier comprehension, this is the essential resource for anyone seeking to understand how the dynamics of biological, social, and other complex systems arise from the characteristics of the agents that make up these systems.
Steven Railsback and Volker Grimm lead students stepwise through the processes of designing, programming, documenting, and doing scientific research with agent-based models, focusing on the adaptive behaviors that make these models necessary. They cover the fundamentals of modeling and model analysis, introduce key modeling concepts, and demonstrate how to implement them using NetLogo. They also address pattern-oriented modeling, an invaluable strategy for modeling real-world problems and developing theory.
This accessible and authoritative book focuses on modeling as a tool for understanding real complex systems. It explains how to pose a specific question, use observations from actual systems to design models, write and test software, and more.
- A hands-on introduction that guides students from conceptual design to computer implementation to analysis
- Filled with new examples and exercises and compatible with the latest version of NetLogo
- Ideal for students and researchers across the natural and social sciences
- Written by two leading practitioners
- Supported by extensive instructional materials at www.railsback-grimm-abm-book.com
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Stochastic, Logistic regression, Verification and validation, Autocorrelation, NetLogo, Lookup table, Ranking (information retrieval), Influence diagram, Satisficing, Utility, Adviser, Agent-based model, Version control, Programming style, Decision analysis, Multi-agent system, Probability, Parameter (computer programming), Disperser, Coefficient of determination, Variable (mathematics), Calculation, Collective behavior, Result, Causality, Calibration, Poisson distribution, Loss function, Sensor, Computational model, Test theory, Model selection, Statistical significance, Parameter space, Replication (statistics), Code review, Scientific modelling, Heuristic, State variable, Stochastic Modeling, Initialization (programming), Uncertainty analysis, Fractal dimension, Estimation, Prediction, Algorithm, Stochastic process, Observation, Statistical model, Decision-making, Dynamic programming, Search algorithm, Simulation, Software testing, Emergence, Conceptual model, Simulation modeling, Behavior model, Poisson point process, Variable (computer science), Software versioning, Decision theory, Reproducibility, Explanation, Collective, Network model, Initial condition, Programming model, Parameter, Sensitivity analysis