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Modeling and Simulation in computer science
Chapters

1Foundations of Modeling in Computer Science

2Mathematical Foundations for Simulation

3Discrete-Event Simulation Fundamentals

4Agent-Based Modeling and Complex Systems

Agents, Environments, and InteractionsEmergence and Self-OrganizationAgent Communication ProtocolsRule-Based vs Utility-Based AgentsTopologies and Network StructuresHeterogeneity and AdaptationLearning in Multi-Agent SystemsCalibration and Validation of ABMsABM Tools and FrameworksApplications in Social SystemsTraffic and Crowd ModelingEcological and Biological ABMsABM Simulation PerformanceReproducibility in ABM ExperimentsEthical Considerations in ABMs

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/Agent-Based Modeling and Complex Systems

Agent-Based Modeling and Complex Systems

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Study agents as autonomous decision-makers, their interactions, and how complex behavior emerges from simple rules.

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Rule-Based vs Utility-Based Agents

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