Foreign Policy Formation
The law of motion captures our intuition about how the consequences of conflict and cooperation unfold in the real world. It formalizes something about how we naturally think about power struggles, even if we've never visualized it in this particular way before.
The law of motion alone, however, is limited in what it can tell us about a system of agents, because it is based on the artificial assumption that none of the agents ever changes their relationships during any of the time steps. We know this is not the case in the real world, where agents are constantly altering their foreign policies in order to improve their position within the power structure. It is to this process that we now turn.
Whereas we previously looked at how agents become stronger or weaker as a result of their relationships with other agents, here we theorize about how they alter those relationships as a result of their position in a given power structure. In other words, we explore foreign policy formation.
This section will cover:
- General Challenge
- Utility Function
- Definition of PrinceRank
- Implications of PrinceRank
- Legal Moves
- Move Selection
- Move Sequences and Distributions
- The Effect of Institutions
There are other ways of reasoning about foreign policy formation that we have not (yet adequately) explored. These include machine learning, Axelrod-style computational tournaments, and mathematical game theory.
Moreover, our implementation assumes that when deciding what move to make, agents only consider the current power structure. One might generalize this and instead allow agents to consider not just the present power structure but its full history as well.