I mean, in this case you just deploy one agent instead of two
If the CAIS view multi-agent setups like this could be inevitable. There are also many reasons that we could want a lot of actors making a lot of agents rather than one actor making one agent. By having many agents we have no single point of failure (like fault-tolerant data-storage) and no single principle has a concentration of power (like the bitcoin protocol).
It does introduce more game-theoretic issues, but those issues seem understandable and tractable to me and there is very little work from the AI perspective that seriously tackles them, so the problems could be much easier than we think.
Even under the constraint that you must deploy two agents, you exactly coordinate their priors / which equilibria they fall into. To get prior / equilibrium selection problems, you necessarily need to have agents that don’t know who their partner is.
I think it is reasonable to think that there could be a band width constraint on coordination over the prior and equilibria selection, that is much smaller than all of the coordination scenarios you could possibly encounter. I agree to have these selection problems you need to not know who exactly your partner is, but it is possible to know quite a bit about your partner and still have coordination problems.
It encourages solutions that take advantage of optimality and won’t actually work in the situations we actually face.
I would be very weary of a solution that didn’t work when have optimal agents. I think it’s reasonable to try to get things to work when we do everything right before trying to make that process robust to errors
The formality of “priors / equilibria” doesn’t have any benefit in this case (there aren’t any theorems to be proven). The one benefit I see is that it signals that “no, even if we formalize it, the problem doesn’t go away”, to those people who think that once formalized sufficiently all problems go away via the magic of Bayesian reasoning.
I think there are theorems to be proven, just not of the form “there is an optimal thing to do”
The strategy of agreeing on a joint welfare function is already a heuristic and isn’t an optimal strategy; it feels very weird to suppose that initially a heuristic is used and then we suddenly switch to pure optimality.
It’s also, to a first approximation, the strategy society takes in lots of situations, this happens whenever people form teams with a common goal. There are usually processes of re-negotiating the goal, but between these times of conflict people gain a lot of efficiency by working together and punishing deviation.
There are ways to get around this. The most common way in the literature (in fact the only way I have seen) gives every agent a belief over a set of common worlds (which contain both the state of the world and the memory states of all of the agents). Then the state of the world is a sufficient statistic over everything that can happen and beliefs about other players beliefs can be derived from each player’s beliefs on the underlying world. This does mean you have to agree upon “possible memory states” before time, or at least both have beliefs that are described over sets that can be constantly combined into a “set of all possible worlds”.