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Project Sid: Many-agent simulations toward AI civilization

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Re: Project Sid: Many-agent simulations toward AI civilization

#161

Post by ValentinA23 »

bbor wrote: post #154
ValentinA23 wrote: post #110

Earlier quoted context omitted.

I don't think "mixture of experts" can be assimilated to a society of agents. It is just routing a prompt to the most performant model: the models do not communicate with each other, so how could they form a society ?

Hmm that's a good point, but IMO the distinction isn't sharp enough to make a big deal over. The core idea of SoM as I see it is that human cognition is often quite decentralized, and that any illusion of a unified self is constructed piecemeal from the outputs of smaller, less-aware subsystems. Generally it's expected that the subsystems communicate with each other, yes, but I think "disproportionately rely on one o…

The opinion I formed during the first few months of GPT4 release was that the society of the mind hypothesis was being disproved by the "maximalist" approach some were undertaking in order to build a true AGI. Turned out composing many LLMs into a cognitive architecture where each one had a specific purpose (memory, planning, etc ...) wasn't scaling.

On the same note, I suggest the following: training a transformer by "slicing" it in group of layers and force it to emit/receive tokens at each of those group's boundaries. What I expect: using text rather than neural activations should lead to decreased performance.

This is something you can observe in our societies: intelligence doesn't compose, you just don't double a group's overall intelligence by doubling the number of members. At best you'll observe decreasing return, at worst intelligence will decrease.

Re: Project Sid: Many-agent simulations toward AI civilization

#162

Post by sirianth »

I'm very confused; is there any emergent behavior in this paper, or it's just like "role-play" based on data about what humans do in the LLM. Like, wouldn't they create novel social structures if they had needs? That doesn't seem so hard to program (the needs part).

Re: Project Sid: Many-agent simulations toward AI civilization

#163

Post by fennecfoxy »

chefandy wrote: post #133
MichaelZuo wrote: post #131

Earlier quoted context omitted.

Nobody will know for sure until a big budget game is actually released with a serious effort behind its NPCs.

I can't see anything that Gen AI NPCs would add unless maybe you're talking about a Sims kind of game where the interactions are the point, and they don't have to adhere to a defined progression. Other than that, it's a chat bot. We already have chatbots and having them in the context of a video game doesn't seem like it would add anything revolutionary to that product. And would that fundamentally stand a chance of…

As someone who has tried a lot of role-play models, I think there is definitely value in what LLMs (or similar tech) can add to NPCs, it's just most people don't know how to prompt for it.

Using the RP models, over time I've found certain things that can guide them to creating better stories; an agent system is much easier to use but even using single character cards it's not hard to stuff them with a narrator and several individual characters in one go. I recently switched from kunoichi (8b, decent) to an Aria derivative (13b, much better).

In the majority of role-play stories I do now, it's super easy to refine the prompt so that characters don't necessarily provide pointless details + avoid all the common tropes, especially with newer models.

Maybe I should make a PoC, would be a fun project. But yeah I agree that chatting to an NPC about its day doesn't necessarily make for great gameplay - but it's relatively easy now to guide it into interesting scenarios/experiences, which _does_ make for great gameplay.

Ie the wife of the hunter you murdered in a fantasy game; normally we just think that we killed a character in a game - but when the hunter's wife decides in the background to train with a sword so that she can avenge her husband, then finally comes to find you and calls you out for murdering her husband - suddenly it's murder, and a revenge story. It's not too hard to prevent a decent model from injecting fluff (like where she bought her sword and how much for) into it.

Edit: just tested this to see what would happen; I first walked into a cottage, grandfather and his young granddaughter, stabbed him in front of her and ran away (spent the next 2 years of "game time" in a forest hiding away). Character motivations updates for the granddaughter were essentially: distraught, vowing revenge, travelling around to hone her skills, speaking with unsavoury types in taverns to find my whereabouts, finding & confronting me, killing me. I was able to query it for "3 dialogue options/actions with percent chances and distinct outcomes in JSON format" which it gave, the chance of her forgiving me was 0.01% which I suppose is fair enough. It did fail to create nice JSON tho, the model is not fine-tuned for that at all.

But it's definitely possibly with multiple loras/prompts/queries to extract dynamic dialogue options, actions, stats, percent chances for plot/story paths etc. LLMs in games definitely need to be managed by a traditional rules based framework, LLM should only be used for the creative bits. Stats/player skill will always determine who wins a fight, but the fight starting because of dialogue or past events could totally be LLM driven.

Re: Project Sid: Many-agent simulations toward AI civilization

#164

Post by fennecfoxy »

logicchains wrote: post #109
bob1029 wrote: post #70

I feel like there is some kind of information theory constraint which confounds our ability to extract higher order behavior from multiple instances of the same LLM. I spent quite a bit of time building a multi agent simulation last year and wound up at the same conclusion every day - this is all just a roundabout form of prompt engineering. Perhaps it is useful as a mental model, but you can flatten the whole thing…

>I feel like there is some kind of information theory constraint which confounds our ability to extract higher order behavior from multiple instances of the same LLM. It's a matter of entropy; producing new behaviours requires exploration on the part of the models, which requires some randomness. LLMs have only a minimal amount of entropy introduced, via temperature in the sampler.

As I've pointed out in the past, I also think it's fair to say that we overestimate human variability, and that most human behaviours and language coalesces for the most part.

Also the creative industry, a talking point being that "AIs just rehash existing stuff, they don't produce anything new". Neither do most artists, everything we make is almost always some riff on prior art or nature. Elves are just humans with pointy ears. Goblins are just small elves with green skin. Dwarves are just short humans. Dragons are just big lizards. Aliens are just humans with an odd shaped head and body.

I don't think people realise how very rare it is that any human being experiences or creates something truly novel and not yet experienced or created by our species yet. Most of reality is derivative.

Re: Project Sid: Many-agent simulations toward AI civilization

#165

Post by fennecfoxy »

InDubioProRubio wrote: post #95
bob1029 wrote: post #70

I feel like there is some kind of information theory constraint which confounds our ability to extract higher order behavior from multiple instances of the same LLM. I spent quite a bit of time building a multi agent simulation last year and wound up at the same conclusion every day - this is all just a roundabout form of prompt engineering. Perhaps it is useful as a mental model, but you can flatten the whole thing…

Maybe we need gazelles and cheetahs - many gazelle-agents getting chased towards a goal, doing the brute force work- and the constraint cheetahs chase them, evaluate them and leave them alive (memory intact) as long as they come up with better and better solutions. Basically a evolutionary algo, running on top of many agents, running simultaneously on the same hardware?

This only works (genetic algo) if you have some random variability in the population. For different models it would work but I feel like it's kind of pointless without the usual feedback mechanism (positive traits are passed on).

Re: Project Sid: Many-agent simulations toward AI civilization

#166

Post by fennecfoxy »

whatshisface wrote: post #57
isoprophlex wrote: post #3

Now these seem to be truly artificially intelligent agents. Memory, volition, autonomy, something like an OODA loop or whatever you want to call it, and a persistent environment. Very nice concept, and I'm positive the learnings can be applied to more mundane business problems, too. If only I could get management to understand that a bunch of prompts shitting into eachother isn't "cutting-edge agentic AI"... But then…

Just so you know, the English noun for things that have been learned is, "lessons."

Learnings is also correct...

Learned can also be learnt (my preference), etc. English has a lot of redundancy, but that's why we love it, right?

Re: Project Sid: Many-agent simulations toward AI civilization

#167

Post by fennecfoxy »

waiquoo wrote: post #147
globnomulous wrote: post #111

Earlier quoted context omitted.

Yup, and "ask" is a verb, God damn it, not a noun. But people in the tech world frequently use "learnings" instead of "lessons," "ask" as a noun, "like" as filler, and "downfall" when they mean "downside." Best to make your peace and move on with life. Just FYI: that second comma is incorrect.

'Gift' vs 'give' also rustles my jimmies. The phrase 'he gifted it to her' doesn't mean anything different from 'he gave it to her'. As a Calvinite, my stance is that 'verbing weirds language'. https://www.gocomics.com/calvinandhobbes/1993/01/25

Nah, give implies it was just given. Something being gifted has specific emotional, cultural and character connotations that differ from simply giving, imo.

Re: Project Sid: Many-agent simulations toward AI civilization

#170

Post by daemon_9009 »

The entire paper demonstrated the results of the simulation or whatever they did. They did not mention how did they achieve this simulation. running 500-1000 LLMs parallely, will take too much computing resources, neither did they prove the claim they made about their parallel architecture. I remeber there was the paper published about an AI town, in which they mentioned clearly how they implemented it. they also released a recording of the simluation along with the real data of the results. If anyone got how they implemented this paper, please tell me.
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