Notes for B.2.8 Constructing Complex Simulations - IB | RevisionDojo
B.2.8 Constructing Complex Simulations Notes
Building Realistic Models with Adaptive Rules
Complex simulations require more than static rules.
They often involve dynamic changes in rules, formulas, or algorithms based on evolving conditions.
Example
In a traffic simulation, speed limits might change based on weather conditions.
If it starts raining, the simulationreduces speed limits and increases stopping distances.
Step-by-Step Example: Ecosystem Simulation
1. Defining the Initial Rules (Prey-Predator)
Predators gain energy by eating prey.
Preyreproduce if they have enough energy.
Predators lose energy over time.
Example
Rule:
If a predator's energy drops to zero, it dies.
If a prey's energy exceeds a threshold, it reproduces.
2. Introducing Dynamic Changes
Seasonal Changes: In winter, prey reproduction rates decrease.
Resource Scarcity: If prey population drops below a threshold, predator starvation rates increase.
Example
Formula Update:
Prey reproduction rate = 0.8 × normal rate during winter months.
Algorithm Change: If prey population < 20, predator death rate increases by 50%.
3. Implementing the Simulation
Use conditional statements to adjust rules dynamically:
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Note
Introduction to Complex Simulations
Complex simulations are advanced models that mimic real-world systems by incorporating multiple variables and dynamic interactions.
Unlike simple models, they require adaptive rules that can change based on evolving conditions.
AnalogyThink of a complex simulation like a video game where the environment and characters adapt to your actions, rather than following a fixed script.
DefinitionComplex SimulationA computational model that mimics real-world systems with multiple interacting variables and dynamic rules.
ExampleIn a weather simulation, factors like temperature, humidity, and wind speed interact dynamically to predict weather patterns.
