Recently I have been thinking about some philosophy in how we model the real world.
For many of us working on the Earth system model, we spent great efforts trying to understand the physical world. For example, we now have a reasonably good idea about how water flows within the system.
Based on our understanding of the physical laws, we built quite a few of process-based models to model and predict different types of systems.
On the other hand, there are also processes that are not “simply” governed by physics. For example, human activities, or some stochastic processes like wildfire.
For some processes, it would be more beneficial to use agent-based modeling (ABM) approach. For example, how an individual tree interacts with its surrounding environment, fighting for water and nutrients, should be possible to be implemented using the ABM.
Other processes, such as animal behavior models, are also similar to ABM.
The new question is: how can we merge the process-based model, or equation-based (EBM) with ABM in the Earth system model. What is more interesting is how can we make use of Artificial Intelligence (AI), which ABM itself is based on, to optimize our model.
To answer these questions, we need to understand the boundary between EBM and ABM and then we can design different processes using either approach. Eventually, we may have a hybrid model for our use.