Complexity Economics: Proceedings of the Santa Fe Institute's 2019 Fall Symposium

We could model agents who had disparate ideas or hypotheses about the situation they were in. They could base their actions on these, and learn which hypotheses worked and which didn’t, getting smarter over time.

But also what’s interesting, we observe that it seems to be that this type of message is, “Good job, well done, we are a team, that’s the way to do it.” Those kinds of messages tend to help in succeeding, in coordinating, in the better outcome.

here: these very actions of agents’ exploring, changing, adapting, and experimenting further change the outcome, and they’d have to then re-adapt and re-adjust.

no more need to have them enforce our contracts.

Most economists now accept the need for more realistic assumptions in economic theory; and methodologies such as network analysis, heterogeneous agent models, evolutionary game theory, and economic lab experiments are becoming standard.

She said much of the finance industry has too narrow a view of its strategy and goals. It often becomes a short-term, almost zero-sum game with many investors focused only on small relative gains won against each other.

But if you think in terms of equilibrium, as I said, there’s a subtle bias with all of us economists. If things are in equilibrium, there’s no way to improve on that, otherwise it wouldn’t be an equilibrium, so we don’t think in terms of people gaming such systems.

Similarly at equilibrium there’s no incentive for any agents to diverge from their present behavior—that’s the definition of an equilibrium. Therefore, exploitive behavior can’t happen. A subtle, muted, unconscious bias precludes ideas of exploitation or collapse.

The first is diverse agents. In markets that means people who have different information, time horizons, and rules of behavior. This explains why behavioral biases are not that important. You can have a lot of little mistakes but the market mechanism deals with them effectively.