# Stuart_Armstrong comments on Stepwise inaction and non-indexical impact measures

• For example, if there is an auxiliary reward for reaching any state except the state before subagent creation, the no-subagent inaction rollout will consist of this state, and the subagent inaction rollout will contain a different state at least once, so subagent creation will be penalized.

This requires identifying what a subagent is in general, a very tricky unsolved problem (which I feel is unsolvable).

There’s another issue; it’s not enough to show that the subagent triggers a penalty. We need to show the penalty is larger than not creating the subagent. Since the penalty is zero after the subagent is created, and since the subagent has very fine control over the rewards (much finer than actions that don’t include creating an intelligent being), creating a subagent might be lower penalty than almost any other action.

It won’t be a lower penalty than the agent doing nothing for ever, of course. But we typically want the agent to do something, so will calibrate the penalty or R_0 for that. And it’s plausible that creating the subagent will have lower penalty (and/​or higher R_0) than any safe “something”.

• I don’t think this requires identifying what a subagent is. You only need to be able to reliably identify the state before the subagent is created (i.e. the starting state), but you don’t need to tell apart other states that are not the starting state.

I agree that we need to compare to the penalty if the subagent is not created—I just wanted to show that subagent creation does not avoid penalties. The penalty for subagent creation will reflect any impact the subagent actually causes in the environment (in the inaction rollouts).

As you mention in your other comment, creating a subagent is effectively switching from a stepwise inaction baseline to an inaction baseline for the rest of the episode. This can be beneficial for the agent because of the ‘winding road’ problem, where the stepwise baseline with inaction rollouts can repeatedly penalize actions (e.g. turning the wheel to stay on the road and avoid crashing) that are not penalized by the inaction baseline. This is a general issue with inaction rollouts that needs to be fixed.