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Instructor-Led Live, Online Training
Real-time, interactive classes taught by SME via web conferencing.
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Individual learning at your own speed, with access to digital materials.
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Customized, face-to-face training sessions delivered at your location.
Curriculum Designed by Experts
The Agent Based Modeling Corporate Training equips professionals with the knowledge and tools to build, analyze, and interpret agent-based models. Participants will explore simulation techniques, model real-world scenarios, and make informed decisions. Ideal for managers, analysts, and executives, this course enhances strategic planning, problem-solving, and operational efficiency, enabling organizations to adapt quickly to market changes and achieve measurable performance improvements.
Agent Based Modeling (ABM) training teaches learners how to simulate complex systems by modeling individual agents and their interactions. It focuses on understanding how simple rules at the micro level create emergent patterns at the macro level. Through hands-on practice with tools like NetLogo, AnyLogic, or Mesa, participants learn to design agents, build environments, run simulations, and analyze outcomes. This training is ideal for professionals seeking data-driven insights for decision-making in business, engineering, healthcare, social sciences, and research.
- Understanding complex adaptive systems
- What is ABM? When and why to use it
- Key components: agents, environment, interactions, rules
- Comparison with System Dynamics & Discrete Event Simulation
- Real-world applications across industries
- Agent attributes and behaviors
- Autonomous decision-making
- Reactive vs Proactive agents
- Learning agents and adaptive behavior
- Agent communication & social networks
- Heterogeneity and stochastic elements
- Types of environments (grid, network, continuous space)
- Movement rules and constraints
- Local vs global interactions
- Feedback loops & emergent phenomena
- Modeling contagion, influence, competition, and cooperation
- Overview of popular ABM platforms:
- NetLogo
- AnyLogic
- Mesa (Python)
- Repast
- Platform selection criteria
- Introduction to the course-specific ABM tool (customized based on learner preference)
- Problem definition & model objectives
- Identifying agent types & states
- Mapping agent rules and interactions
- Building environment structure
- Time scheduling & simulation cycles
- Setting global parameters & assumptions
6.1 Creating Agents
- Defining breeds
- Assigning attributes
- Designing behavior procedures
6.2 Environment Setup
- Building grids/networks
- Importing GIS data (if required)
6.3 Designing Interactions
- Movement, communication, influence
- Resource exchange
- Collision & conflict resolution
6.4 Model Visualization
- Interface design
- Animation & data displays
- Plotting real-time results
- Parameter calibration techniques
- Sensitivity analysis
- Statistical validation
- Debugging ABM
- Ensuring model reliability
- Importing datasets
- Running experiments and scenarios
- Parameter sweeps and Monte Carlo simulations
- Generating outputs for analysis
- Complex networks & graph-based modeling
- Social influence and contagion models
- Evolutionary algorithms in ABM
- Machine learning + ABM hybrid systems
- Multi-layer and multi-scale modeling
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Customized trainings to understand specific project requirements
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Free Agent Based Modeling Corporate Training Assessment
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Agent Based Modeling Corporate Training Certification
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