Draft papers for REALab and Decoupled Approval on tampering

Hi everyone, we (Ramana Kumar, Jonathan Uesato, Victoria Krakovna, Tom Everitt, and Richard Ngo) have been working on a strand of work researching tampering problems, and we’ve written up our progress in two papers. We’re sharing drafts in advance here because we’d like to get feedback from everyone here.

The first paper covers:

How and when tampering problems might arise in the real world
Key assumptions in standard RL frameworks we relax to allow modeling tampering
How we model and measure tampering empirically, through our internal platform REALab, and
How we formalize tampering problems, through our Corrupt Feedback MDP formalism

We particularly hope it clears up the concept of tampering (and why “but the agent maximized its given reward function” typically assumes the wrong framing), and internally, we’ve found REALab to be a useful mental model.

The second paper describes:

Decoupled approval, an algorithm closely related to approval direction and Counterfactual Oracles, and designed to be straightforwardly compatible with standard deep RL
An analysis of this algorithm (within the CFMDP formalism), and
Empirical validation (in REALab)

We’d love to get feedback on these; the current drafts are viewable in this Google Drive folder. We’re happy to discuss these on whichever of LessWrong/Alignment Forum/Google Drive comments, and would prefer to keep discussion on these forums for now, as we’ll share the papers more widely after they’re posted on arXiv in a few weeks. Looking forward to hearing your thoughts!