it's actually a great game with tons of potential since i'm done with the main story (for now), i'm focusing on building a base, where i found some bugs 1. sometimes, their storages will get "full" even though theres 1-2 items 2. their pathfinding is kinda broken, specially-

Completed the obstacle avoidance(no pathfinding). Using different radii and obstacles together is more expensive, but the same applies to RVO2. Further optimizations are probably out of my league, so I’ll take these results as a win. Next big step: multithreading. 😄

Clip is ten years old, Sam forged his own route and became more successful than the guy with the shitty architecture. I remember when the right used to idolize pathfinding over careerism. Depressing

bot minions should not be a thing either pc2 has a horrible track record with minion pathfinding

@TrudoJo, your June 13 thread (and repeated posts) include several false and slanderous claims about me and my work. My work is public across GitHub (LabyrinthCoderDev) and openly shared on X—parts here, parts there, fully visible to anyone who looks. The experimental Python prototype with its maze and pathfinding engine is available for inspection, running where runnable, forking, or critique. Nothing is hidden. You claimed I admitted to stealing from Void OS, put my name on it, and expected credit. That is not accurate. Components came from open group chats, shared unsigned work, and public sources—standard in this space. I have always been transparent that my material is public knowledge and free for others to use or discard as they see fit. The whole larper comment has been misunderstood from the start. No side-by-side diffs or verbatim copies have been shown, only interpretive framing. If you have specific verbatim evidence, post the links. You also claimed the last version of Labyrinth had “so many holes” and unsupported claims, that I got defensive when you pointed them out in your penetration test report, preemptively messaged about sharing the system, ignored your prior use of “Labyrinth” with Vault Mother, tried to cozy up to her, and played dumb about the confrontation while others implied you stole from me. Those issues from your penetration test report (Reality Gate bypass risks, sensor spoofing vectors, governance flooding, SOFT mode labels, placeholder values like betti_1, etc.) were already publicly tracked in my Known Gaps folder and Assumption Closure Protocol with clear states and dependency chains. The report was a solid static analysis of a shared snapshot and revealed no new zero-days. I have iterated and shared updated versions since. All prototypes have gaps; documenting and closing them is the work. I did not get defensive—I engaged with the feedback. There was no playing dumb; I’m honestly just slow sometimes on processing things, and there’s a lot going on in the background that I’m unaware of. When I pointed out the word “Labyrinth,” I was only wondering if it related to my work—I added the “I don’t know” emoji, shrugging my shoulders because I wasn’t going to make any assumptions. The rest of that narrative does not match the record. I am iterating openly with runnable artifacts and transparent gap tracking. I remain happy to collaborate or mutually review work on the actual code. You keep slandering me publicly across multiple posts. If your concern is genuine architectural integrity, let’s focus there instead of continued character attacks and misframing. @LastingCzardd @TheVaultMother @LilithDatura

Even pathfinding and recon is never alone. If you take casualties and wounded its always wise to just run.

We didn't program how to steer, forage, or mate. They have no pathfinding code. Instead, they learn using a dopamine reward system. When they do something that satisfies their hunger or thirst, their brain strengthens that behavior. (2/3)

Unironically yes I enjoyed being forced to plan my routes, being allowed to bypass the enemy fights with clever pathfinding, and being rewarded for noticing hidden details. With totk I have a dozen ways to fly into the air and just pass over any obstacle. It wasn't rewarding.

Meet my trusty follower. Animation blending is in, so I thought I'd put that pathfinding I built earlier into action and make a basic NPC.

still working at target prioritization and pathfinding

Normally outgoing LN pathfinding isn't a problem, in practice long stretches can hit 100% success rates. In decentralized sends, that can dip. A solve is seen on the receiver side: balance channels to improve inbound. On the sender side a trick is to use bad inbound peers to send

LOL We'll be implementing a system to improve settler pathfinding soon, they can be a bit... lost at times!

flat capacity 4x throughput says pathfinding is getting better at routing around imbalances. the plumbing is maturing faster than the pipes are growing.

I have been experimenting with this for a couple of years via llm-consortium. There was a paper by google called Mind Evolution which did similar. There are large gains for some problems that can be reduced to search like pathfinding and scheduling.

Most companies are panic-buying AI agents without thinking about revocation, payments, or fraud. We built a simulation of RL pathfinding gone wrong → signal.meltke.com/rl-pathfin… What’s the scariest unintended behavior you’ve seen from agents? 👇

What matters here isn’t liquidity availability, it’s pathfinding quality across fragmented systems.