Table 3. Complexity aspects enabled per simulation modeling technique.
| Markov Model | System dynamics | Micro-Simulations | Discrete Event Simulation | Agent-Based Models | |
|---|---|---|---|---|---|
| Individualization | X | X | ✓ | ✓ | ✓ |
| Dynamism | ✓1 | ✓ | ✓ | ✓ | ✓ |
| Interaction | ✓ | ✓ | ✓ | ✓ | ✓ |
| Interference | X | X | X | ✓ | ✓ |
| Intelligent Adaptation | X | X | X | X | ✓ |
| Soft variables | X | ✓ | X | X | ✓ |
| Simultaneity of events | X | X | X | ✓ | ✓ |
| Influence of historical occurrences | X2 | ✓ | ✓ | ✓ | ✓ |
| Emergence | X | X | X | X | ✓ |
1 The technique can incorporate dynamic changes over time, but not endogenous feedback loops.
2 Even though the ‘Markovian Property’ defines that transition probabilities will depend only on the current state and not on previous states thus eliminating the possibility of having ‘Memory’, researchers can overcome this by incorporating tunnel states and parallel models.