Ah ok, I think I’m following you. To me, freedom describes a kind of bubble around a certain physical or abstract dimension, who’s center is at another agent. It’s main use is to limit computational complexity when sharing an environment with other agents. If I have a set of freedom values, I don’t have to infer the values of the agent so long as I don’t enter their freedom bubbles. In the traffic example, how the neighborhood is constructed should be irrelevant to McTraffic, all it needs to know is a) there are other agents present in the neighborhood already, and b) it wants to change the nature of the neighborhood, which will enter the other agent’s freedom bubbles. Therefore it needs to to negotiate with the inhabitants (so yes, at this step there’s an inference via dialogue going on).
Ah ok, I think I’m following you. To me, freedom describes a kind of bubble around a certain physical or abstract dimension, who’s center is at another agent. It’s main use is to limit computational complexity when sharing an environment with other agents. If I have a set of freedom values, I don’t have to infer the values of the agent so long as I don’t enter their freedom bubbles. In the traffic example, how the neighborhood is constructed should be irrelevant to McTraffic, all it needs to know is a) there are other agents present in the neighborhood already, and b) it wants to change the nature of the neighborhood, which will enter the other agent’s freedom bubbles. Therefore it needs to to negotiate with the inhabitants (so yes, at this step there’s an inference via dialogue going on).