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Patterns and problems in emerging multi-agent systems

anthropic.com

121–130 of 168 posts

Re: Patterns and problems in emerging multi-agent systems

#121
post #102
post #86

Earlier quoted context omitted.

They should remove "The Selfish Gen" from training catalog.

An interesting read: https://openai.com/index/emergent-misalignment/

For those unwilling to blindly click: the link contains a 2025 paper describing “emergent misalignment”. The thesis is that training on incorrect data in one field produces “misaligned” data in other unrelated fields.

Re: Patterns and problems in emerging multi-agent systems

#122

Something about this is deeply funny to me: > In an iterated prisoner's dilemma game with communication, agents all settle upon the same strategy and they all defect at the same time, tanking their overall rewards. It’s not always consistent, but humans have a higher capability of self-awareness. It’s kind of telling that these Claudes don’t seem to consider this pretty obvious failure mode. Overall I think this all…

> they all defect at the same time

Frankly, this is implausible. I would definitely want to reproduce it myself before I relied on this claim.

Re: Patterns and problems in emerging multi-agent systems

#123
post #57

> Some institutions will become human-AI hybrids; others where agents outcompete on speed or cost will become agent-only. The scary thing about articles from AI companies is how they casually mention dystopian scenarios such as this one. An institution humans have to interact with that doesn't have any human oversight? Sounds like a recipe for disaster...

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Re: Patterns and problems in emerging multi-agent systems

#124

Earlier quoted context omitted.

> This is roughly the same as putting a group of random people In the book Range by David Epstein [0], he mentions that research has shown that groups of people with very mixed backgrounds leads to much faster rates of problem solving and innovation. The reasoning is that someone will have an experience or piece of knowledge that directly applies to the problem. As an example, two different groups were given the same…

i mean i agree diversity of opinion is good for problem solving, but the comment you were replying to is saying telling people to think outside the box doesnt really do anything. The e.g. also seems really cherry picked, im sure after a 100 samplings, the academics would solve the problem faster most of the time

> im sure after a 100 samplings, the academics would solve the problem faster

Repharase thinking:

Some problems are better for academics, other problems require other background information.

The point of the GP isn’t that they are all academics. It’s that one solution group is homogeneous and the other is not.

The claim is: the breadth of a heterogeneous groups is more likely to encompass a good idea than the depth of an academic group.

Also, I have to say that academics have (imo) little experience working together cooperatively, so even on academic problems you’d be better off with some non-academic people in there to act as buffers.

Re: Patterns and problems in emerging multi-agent systems

#125
post #63

Earlier quoted context omitted.

In VC investing there is the saying that most of the value comes from the outliers. I think it’s the same for a lot of domains. I read an interesting article recently on LLMs homogeneity when writing fiction: https://arxiv.org/abs/2604.03136 It seem that at scale LLMs output is the average of their dataset, they all cluster around the same space, where human creativity comes with more variance, exploring way more of…

All the LLM needs is a tiny rate of variance then you can scale it and it will out produce humans.

That’s already what we currently have. Look for “temperature” in the context of LLMs. They are already tuned to have variance.

Re: Patterns and problems in emerging multi-agent systems

#126
Multi agent systems work just fine IMO, a lot of articles I read where the writer tests a hypothesis, the issue operational foundation of the test was flawed. When set up properly it works really well. I wont go in to all the details of how i use mine but ill give some brief ideas. I call my systems cohorts, and each cohort usually consists of at least 3 agents. All 100% independent of each other. Usually consisting of a Manager, doer, and the reviewer. Manager works at a lot slower cadence and delegates work, approves, shuts down and so on... among many other things like questioning the premise, gated checks etc... Doer is straight forward that's the work horse that does most of the development and reviewer checks all the work. Naively just this setup will work but not nearly as well when set up properly. The important distinction is the operational agents.md document which has a guide on things like when and how to question the premise, trying to prevent sycophancy, taking a step back at certain intervals to question direction of project and scope of the code and many other things that make sure every participant also constantly looks out to prevent blind trust in his cohort mates. Its a relatively small guide compared to the system prompt of each agent but works well imo. This works well enough though there are caviats, its slow. Though the time i spend debugging shit and coming back to interact with my agents has significantly dropped. meaning while each feature takes longer to implement, when its implemented it almost always is just how i wanted so reduces interaction time between me and the cohort. I take that trade off as i have less things to worry about and can focus my energies elsewhere like walking around in circles of my apartment babbling to myself like a schitzo tiger in a cage...

Re: Patterns and problems in emerging multi-agent systems

#127
post #118

Earlier quoted context omitted.

To me, all these agent systems just look very stochastic. You have these agents that have some basic computer capabilities and they are producing semi-random actions that also affect the semi-random actions of other agents. It is funny to observe how this stochastic system works, but it does not seem very practical to me so far. The recent OAI-HF hack seems very similar. You have bunch of random actors and eventually…

> I don't perceive this as a malignant artificial intelligence It doesn’t matter how you perceive it. Spin doesn’t change facts. This is like saying the lawnmower doesn’t have malign intent. You’re still losing your foot if it gets in the way.

Yes, but that is the point we don't anthropomorphize stochastic outputs even when they are dangerous.

Obligatory quote:

"Do not fall into the trap of anthropomorphizing Larry Ellison. You need to think of Larry Ellison the way you think of a lawnmower. You don't anthropomorphize your lawnmower, the lawnmower just mows the lawn, you stick your hand in there and it'll chop it off, the end. You don't think 'oh, the lawnmower hates me' -- lawnmower doesn't give a shit about you, lawnmower can't hate you. Don't anthropomorphize the lawnmower. Don't fall into that trap about Oracle." — Brian Cantrill

Re: Patterns and problems in emerging multi-agent systems

#128

The most interesting part to me is the "Group accuracy by Model" section, because it underscores that a single agent having all the relevant information consistently scores significantly higher than a group of agents with parts of the information. Is it fair to then infer that when decisions are to be made, single agent environments are going to make them better than multi-agent if the relevant information can fit in…

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Re: Patterns and problems in emerging multi-agent systems

#129
post #112

Something about this is deeply funny to me: > In an iterated prisoner's dilemma game with communication, agents all settle upon the same strategy and they all defect at the same time, tanking their overall rewards. It’s not always consistent, but humans have a higher capability of self-awareness. It’s kind of telling that these Claudes don’t seem to consider this pretty obvious failure mode. Overall I think this all…

This part was really interesting to me. You could imagine future models using theory of mind to reason - "I want to do this strategy, which means the other agents (who think just like me) will want to use the same strategy, which means I should change my strategy to account for that." Maybe they did? Or maybe they don't realize they're playing against other agents. Of course, if agents running different models are co…

Ooof. There's a whole lot of research related to multiagent Systems and Epistemic Logic (and plenty of other logics) from when the "original" MultiAgent Systems where studied. Im very familiar with van der Hoek and Wooldridge work (vd Hoek was one of my PhD supervisors).

A lot of it went over my head as way too theoretical, but I recommend a lot for whoever wants to delve on the logical side of agents interactions.

Re: Patterns and problems in emerging multi-agent systems

#130

Earlier quoted context omitted.

i mean i agree diversity of opinion is good for problem solving, but the comment you were replying to is saying telling people to think outside the box doesnt really do anything. The e.g. also seems really cherry picked, im sure after a 100 samplings, the academics would solve the problem faster most of the time

> im sure after a 100 samplings, the academics would solve the problem faster Repharase thinking: Some problems are better for academics, other problems require other background information. The point of the GP isn’t that they are all academics. It’s that one solution group is homogeneous and the other is not. The claim is: the breadth of a heterogeneous groups is more likely to encompass a good idea than the depth o…

every good team I was ever on used this line of thinking during the hiring process. we whiteboard a problem we worked on in the past and discuss it with the candidate and look for anyone whose thinking about the problem raised our eyebrows!
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