Modeling and Simulation in computer science

Chapters

1Foundations of Modeling in Computer Science

Introduction to Modeling Concepts Abstraction and Granularity Model Types and Taxonomies Requirements Elicitation for Models Model Formulation and Assumptions Model Validation vs Verification Model Reuse and Component Libraries Model Life Cycle and Lifecycle Phases Philosophies of Modeling in CS Formal vs Informal Modeling Model Evolution and Versioning Scalability Considerations in Modeling Ethical and Social Implications of Models Interdisciplinary Modeling Case Study: Building a Simple Model

2Mathematical Foundations for Simulation

3Discrete-Event Simulation Fundamentals

4Agent-Based Modeling and Complex Systems

5System Dynamics and Continuous Modeling

6Numerical Methods and Scientific Computing for Simulation

7Stochastic Processes and Uncertainty Quantification

8Data Structures, Algorithms, and Simulation Efficiency

9Simulation Programming Languages and Frameworks

10Verification, Validation, and Experiment Design

11Performance Analysis and Optimization of Simulations

12High-Performance Computing and Parallel Simulation

13Data Management, Reproducibility, and Experiment Tracking

14Visualization and Communication of Simulation Results

15Applications and Case Studies in Modeling and Simulation

Courses/Modeling and Simulation in computer science/Foundations of Modeling in Computer Science

Foundations of Modeling in Computer Science

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Introduce core ideas of modeling, abstraction, and the model lifecycle to establish a solid base for all simulation work.

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Philosophies of Modeling in CS

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