- > Werld drops 30 agents onto a graph with NEAT neural networks that evolve their own topology, 64 sensory channels, continuous motor effectors, and 29 heritable genome traits. communication bandwidth, memory decay, aggression vs cooperation — all evolvable. No hardcoded behaviours, no reward functions. - they could evolve in any direction.
In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6.
"What are you doing?", asked Minsky.
"I am training a randomly wired neural net to play Tic-tac-toe", Sussman replied.
"Why is the net wired randomly?", asked Minsky.
"I do not want it to have any preconceptions of how to play", Sussman said.
Minsky then shut his eyes.
"Why do you close your eyes?" Sussman asked his teacher.
"So that the room will be empty."
At that moment, Sussman was enlightened.
- I think it looks fun, but at the same time I really wish you had written the readme yourself and not using an llm. My view: if you can’t be bothered to write it yourself, why should I read it myself?
- AGenetic life for Gq7GMMVxvhbmj1D7pGUcxuWTAXkdvGZXWSFdhvsGpump
https://github.com/nocodemf/werld
- this reminds me of Polyworld by Larry Yaeger, an artifical life sim where each creature has a vision system. i played around with this back in the early 2000s though the hardware i had access to was basically insufficient to run it in any real way. it's nice to see its development has continued.
https://en.wikipedia.org/wiki/Polyworld
- I love emergent behaviour and story telling. Anyone who has played City builders like Sim City or roguelikes like Dwarf Fortress knows how interesting, fun and even informative they can be.
In a world where setting them up and letting rogue agents run rampant becomes relatively low cost and fast, I think focusing on the desired outcomes, the story telling and specially the UX for the human user, is key and maybe we can take some learnings from Will Wright on "Designing User Interfaces to Simulation Games" [1].
I'm going to be unable to do much this weekend so I can't say I'll try check this out (yet?) but I'd be interested in your own experiences so far. Any surprises? Things you'd like to do next? What's most fun/challenging?
An actual report/writeup will probably resonate more than a repo for people who can't check it out easily or are not willing to.
- [1] https://donhopkins.medium.com/designing-user-interfaces-to-s...
- > No hardcoded behaviours, no reward functions. - they could evolve in any direction.
If they can hack their reward functions won't this always converge on some kind of agentic opium den?
by e1ghtSpace
1 subcomments
- I like the idea of evolving agents from scratch with no "learning", they just evolve their ability to survive in the environment. Maybe one day it'll be advanced enough to see life evolve.
How does the narrative story generator work?
I played around a bit with NEAT networks, and tried to create a bitcoin trading bot, but the best I could do was a +10% gain over many months. I was hoping for at least 30% each month. Oh well, I guess it doesn't all just depend on past price history.
by fuzzythinker
0 subcomment
- Some NEAT related links:
https://sharpneat.sourceforge.io/ - OSS in github, well maintained
https://weightagnostic.github.io/ - WANN
by fd-codier
1 subcomments
- No images in the README...
- Updated based on feedback — added screenshots to the README and upgraded the story generator for a better narrative. Thanks for all the input.
- Arguably a powerful demonstration of why even simple creatures make use of parenting as a strategy to improve the success of their offspring.
by AreShoesFeet000
1 subcomments
- It is impossible to enforce a world free of heuristics, but this is certainly very cool.
Reminds me of that Black Mirror episode with the circular QR code.
by midnitewarrior
1 subcomments
- This is one or two steps removed from Thronglets.
- This seems to start with 2 agents, and then all of their offspring die immediately. Any hints?
by nimbus-hn-test
0 subcomment
- [dead]
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