Figure 2

Toy example of an innovation spreading among four agents that are changing their positions in the suitability landscape continuously in time. Agents that adopted the innovation are colored in red and non-adopters are shown in yellow. We start with an updated network at time \(t^{*}\) with one agent knowing about the innovation. Then, the interaction network and resulting adaption rates are updated every Δt, until the next adaption event happens at time \(t^{**} = t^{*} + \tau\), i.e. when the total adaption rate integrates to \(\alpha\sim \mbox{Exp}(1)\). The network and rates are updated at time \(t^{**}\). Similarly, between \(t^{**}\) and the next adaption event, fixed updates for the adaption rates and network are done at times \(t^{**} +\Delta t\), \(t^{**} + 2\Delta t\) etc.