My name is Ernesto Carrella. I am a Post-Doc at the Oxford University Centre for the Environment, working under Richard Bailey on an agent-based model of fishery management. I earned my Ph.D from the [Department of Computational Social Science] at George Mason University.
I build and maintain POSEIDON, yet another agent-based model of fisheries. I designed POSEIDON with 3 major priorities in mind:
- Policy planning
- Flexiblity to details
Heuristics provide a happy balance between the need to model adaptation to new policy (what optimizing agents promise) versus the need to be a realistic representation of what actually happens ( what statistical or interview-driven agents provide).
I think general heuristics can be both robust to the Lucas critique and easily calibrated given real data.
Once agents are adaptive, it’s always a good idea to look for policies that drive agents towards the right adaptation. I think the idea of exploring agent-based models by hooking them up to optimization routines is extremely powerful.
I also wanted to build a model that could be both used as an intuition pump and for applied work by seamlessly adding details. I didn’t want a “toy” model and a separate “real” one. POSEIDON can test basic textbook examples and then scale to large applications.