SPEAKER_00 says constrained reinforcement learning can impose an expected constraint across a thousand trajectories, such as limiting the frequency of being in the wrong lane.

“That's a constraint because write it down exactly the same as saying, well, don't be in there more than five seconds or whatever. Rather in mouse constraint reinforcement you say, well in expectations, if you take a thousand trajectories, don't be in the wrong lane too often or something like this. And there's another,”