Difference between revisions of "Purpose"
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The experimental approach helps to measure the performance of different modes of governance and to identify the relevant parameters, influencing agents' decision and, finally, system dynamics. | The experimental approach helps to measure the performance of different modes of governance and to identify the relevant parameters, influencing agents' decision and, finally, system dynamics. | ||
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: Go to the next page: [[Components and Features]] | : Go to the next page: [[Components and Features]] | ||
Latest revision as of 09:57, 28 March 2023
SimCo allows to model and to simulate the dynamics of complex systems where large numbers of heterogenous agents act (autonomously) and interact with each other as well as with the (physical) infrastructure. This way two different governance issues can be investigated.
Risk management
Operators aim at reducing undesirable external effects (e.g. pollution) or system breakdown (e.g. congestion).
System transformation
Political measures are induced to promote a regime change (e.g. towards sustainable mobility).
Modes of governance
In both cases control aims at changing the system state by means of influencing the behaviour of individual agents. SimCo allows to experiment with different modes of governance, especially
- self-coordination (operators do not intervene)
- soft control (relying on incentives)
- strong control (enforcing changes by more compelling measures)
The experimental approach helps to measure the performance of different modes of governance and to identify the relevant parameters, influencing agents' decision and, finally, system dynamics. Test
- Go to the next page: Components and Features