CS620 Subjective

CS620 Important Topics

🔹 What does Imminent Event mean?

An imminent event is the next event that’s going to happen in a simulation. It's the one with the closest (earliest) scheduled time.

🧠 Think of it like: In a to-do list, the task with the nearest deadline is your "imminent task" — same for events in simulations.

🔹 What is a Complex Adaptive System?

It’s a system made of many parts (agents) that interact and adapt to each other and the environment.

📌 Properties:

Emergence: New behaviors appear from simple rules. Adaptation: System changes over time. Non-linearity: Small changes can cause big effects. Feedback Loops: System gets feedback from its own actions. Self-Organization: No central control, system organizes itself.

🧠 Example: Ant colony, traffic system, stock market.

🔹 Role of Verification in Model Correctness:

Verification checks: 👉 “Are we building the model correctly?”

It ensures:

No coding mistakes Logic flows correctly Model works as per design

🧠 Simple Tip: “Verification = Checking code logic”

🔹 Example of Distribution in Physical Basis:

Example: The Normal Distribution is used to model:

Height of people Measurement errors Temperature changes

🧠 It’s based on natural/physical behaviors that are common in real life.

🔹 What is Imperfection Debugging?

It's the process of fixing errors or unexpected behaviors in a simulation model caused by:

Logical flaws Wrong assumptions Programming mistakes

🧠 Think of it as finding bugs that make your model give wrong or weird results.

🧾 Long Questions (Explained Simply)

✅ Macro-validation of Agent-Based Modelling:

Checks if the overall behavior of your agent model matches real-world data or expected patterns.

📌 Example: If you simulate traffic, macro-validation means checking if your simulation matches real-world traffic trends — not just individual car behavior.

✅ What is Common Random Number (CRN)?

A technique used to compare two models or systems fairly by giving both the same random inputs.

📌 Used in:

Simulation experiments Reducing variability 🧠 Like giving two players the same dice rolls to compare their strategies.

✅ Bernoulli Distribution: · It’s a distribution with only two outcomes: · ✔️ Success (1) · ❌ Failure (0)

📌 Used when:

Tossing a coin (Heads/Tails) Yes or No type problems

✅ Chaos Theory:

It studies systems that:

Are deterministic (rule-based) But behave in unpredictable ways due to sensitivity to initial conditions

🧠 Small change in input → Big change in output 📌 Example: Weather forecasting, Butterfly Effect

🔥 Paper Questions (Simplified)

✅ Agent-Based Modeling (ABM) Properties:

Agents act independently They interact with each other Behavior is rule-based System behavior emerges from agent actions

Agent: A self-acting entity in a simulation (e.g., a car, person, etc.) Observer: Watches the simulation, doesn’t take part