Hi everyone! My name is Ram Rachum, and this is my first post here :)
I'm an ex-Google software engineer turned MARL researcher. I want to do MARL research that promotes AI safety. You can read more about my research here and sign up for monthly updates.
I had an idea for a project I could do, and I want you to tell me whether it's been done before.
I want to create a demo of Stuart Russell's "You can't fetch the coffee if you're dead" scenario. I'm imagining a MARL environment where agent 1 can "turn on" agent 2 to prepare coffee for agent 1, and then agent 2 at some point understands how to prevent agent 1 from turning it off again. I'd like to get this behavior to emerge using an RL algorithm like PPO. Crucially, the reward function for agent 2 will be completely innocent.
That way we'll have a video of the "You can't fetch the coffee if you're dead" scenario happening, and we could tweak with that setup to see what kind of changes make it less likely or more likely. We could also show that video to laypeople, and it will likely be much easier for them to connect to such a demo rather than to a verbal description of a thought experiment.
Are there any existing demonstrations of this scenario? Any other insights that you have about this idea would be appreciated.
I'll check that out, thank you.
Could you please expand on the hot take, please? Consider that a big part of the appeal for me is just being able to display the problem and make it relatable for people who aren't from the field.
Also, what kind of richness do you think makes the qualitative difference that you allude to? If the world was 3D or had continuous action or had more game mechanics, would that have made the difference for you?