Model thinking lecture note (2)

Aggregation

(1)Simple rules combine to form anything. In agent based model, just some simple rule that every agent follows would have a complicated outcome.

(2)It from bit. Every difficult system would have the most basic question and it only has "yes" or "no" answer.

(3)Complexity and randomness require interdependency. For example, every agent makes their decision from others.

Multi-Criterion decision-making model

We can make a table like this:

Remember that we don't use model to tell how we make choice but we model to know what we really want.

Spatial model

Remember that some features can not use this model cause maybe some is the more the better or the less the better.