What can the mathematics of networks, social interactions and agent-based modelling tell us?
Use of agent-based modelling to either
- Better understand the type of networks and agents involved plus the way their connections work, or to;
- Make predictions about the impact/success of new interventions and the changes they might generate
This approach runs the risk of predestination - that is, the chosen parameters pre-define the outcome, rather than 'emergence' occurring where new states appear that were not predicted. It may also bias the network towards individuals and ignore impact of technology or infrastructure.
Networks of interacting agents (e.g. people or companies) tend to be complex systems with settled states that have the potential for rapid change into new states. The principles (and in fact physical realities) are the same as those underlying the concept of tipping points.