All of rorygreig's Comments + Replies

Thanks again John for giving this talk! I really enjoyed the talk at the time and was pleasantly surprised with the positive engagement from the audience. I'm also pleased that this turned into a resource that can be re-shared.

I suppose I can imagine an architecture that has something like a central planning agent that is capable of having a goal, observing the state of the world to check if the goal had been met, coming up with high level strategies to meet that goal, then delegating subtasks to a set of subordinate sub-agents (whilst making sure that these tasks are broken down enough that the sub-agents themselves don't have to do much long time-horizon planning or goal directed behaviour).

With this architecture it seems like all the agent-y goal-directed stuff is done by a s... (read more)

Good points, however I'm still a bit confused about the difference between two different scenarios: "multiple sub-agents" vs "a single sub-agent that can use tools" (or can use oracle sub-agents that don't have their own goals).

For example a human doing protein folding using alpha-fold; I don't think of that as multiple sub-agents, just a single agent using an AI tool for a specialised task (protein folding). (Assuming for now that we can treat a human as a single agent, which isn't really the case, but you can imagine a coherent agent using alpha-fold as ... (read more)

I agree that initially a powerful AGI would likely be composed of many sub-agents. However it seems plausible to me that these sub-agents may “cohere” under sufficient optimisation or training. This could result in the sub-agent with the most stable goals winning out. It’s possible that strong evolutionary pressure makes this more likely.

You could also imagine powerful agents that aren’t composed of sub-agents, for example a simpler agent with very computationally expensive search over actions.

Overall this topic seems under-discussed in my opinion. It would be great to have a better understanding of whether we expect sub-agents to turn into a single coherent agent.

The video of John's talk has now been uploaded on YouTube here.

I really enjoyed this dialogue, thanks!

A few points on complexity economics:

The main benefit of complexity economics in my opinion is that it addresses some of the seriously flawed and over-simplified assumptions that go into classical macroenomic models, such as rational expectations, homogenous agents, and that the economy is at equilibrium.  However it turns out that replacing these with more relaxed assumptions is very difficult in practice.  Approaches such as agent-based models (ABMs) are tricky to get right, since they have so many degrees... (read more)

The workshop talks from the previous year's ALIFE conference (2022) seem to be published on YouTube, so I'm following up with whether John's talk from this year's conference can be released as well.

This is a really interesting point that I hadn't thought of!

I'm not sure where I land on the conclusion though. My intuition is that two copies of the same mind emulation running simultaneously (assuming they are both deterministic and are therefore doing identical computations) would have more moral value than only a single copy, but I don't have a lot of confidence in that. 

Yes it is indeed a hybrid event! 

I have now added the following text to the website:

The conference is hybrid in-person / virtual. All sessions will have remote dial-in facilities, so authors are able to present virtually and do not need to attend in-person.

This was in our draft copy for the website, I could have sworn it was on there but somehow it got missed out, my apologies!

Update: The submissions deadline for this Special Session has been extended to 13th March.

Hey, one of the co-organisers of this special session here (I was planning to make a post about this on LW myself but OP beat me to it!).

Clearly I am biased, but I would highly recommend the ALIFE conference (even outside the context of this special session). I published a paper there myself at ALIFE 2021 and really enjoyed the experience.

It has a diverse, open-minded and enthusiastic set of attendees from a wide range of academic disciplines, the topics are varied but interesting. Regarding being in touch with reality, this is harder to comment on but it ... (read more)

I have been thinking about this for quite a while. In particular this paper which learns robust "agents" in Lenia seems very relevant to themes in alignment research: Learning Sensorimotor Agency in Cellular Automata

Continuous cellular automata have a few properties which in my view make them a potentially interesting testbed for agency research in AI alignment:

• They seem to be able to support (or make discoverable) much more robust and complex behaviours and agents than discrete CAs, which makes them seem a bit less like "toy" models.
• They can be differenti

He has written a paper on this too, link here.