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You are welcome to post where you think is best. Codewise, a good improvement @ffm2 would be packing your mod as an extension of localratings. In practice, include (only) your additions in a mod, and add localratings as a dependency. It will simplify maintaining and distributing the code. It will also ensure compatibility with the base mod across versions. Up to you - but I think your work will benefit!

Hi and welcome to the forum! Unfortunately, the only way I am aware is to actually select the ship and see the garrisoned number of people. There has been multiple suggestions to modify that so it will be addressed.

Update on the LR_Teambalancer: Removed the game setup page .xml including the buttons to balance the teams and evaluate the current teams. The new popular mod extraplayers overrides it. Commands in the game setup: /balance /evaluate /rate playername 2000 Also to clarify a common confusion: The teams are paired by the conservative rating e.g. 1800 - 400 = 1400 The winning estimation is calculated by the raw rating e.g. 1800 Might be confusing, but my attempt to simplify it wasn't better (e.g. using only conservative). Also if @Mentula doesn't like me to hijack the thread, just say if I should detach or so. IMO it belongs here best. LocalRatings_Teambalancer.zip

Updated for R28. Most notable change: Game decided announcement.

Group placement eventually loaded. But it was stuck at 6% for a long time. With that said, it only loaded after host ended game

This is some legit R&D for better 0ad bot. Hopefully it will be atleast as good as a 1500 player or even more. I cant really wait for 1 hour before I get chance to play (Tight time constraints these days). Will be really cool if I can get into high quality match, anytime, on demand. Something not possible with a 700 bot like petra

Six months has passed. Development of stevenlauBot did not stop, but I have been dealing with a really difficult problem - optimal field placement around CC. The algorithm improved over and over, and now reaches an optimal solution worth sharing. Before I go into technical details, here are some screenshots of optimal placements in random Mainland. Pink represents the region where we can place field freely, and blues are the fields. Now I am writing some technical details. I first define Gap and Hang. Gap Ideally we want to let a field to touch (snap) the CC (or actually any dropsite), so that farmers can efficiently drop resources without walking. However, since farmers have a size and dropping range, we can actually leave a gap (around 5.6m) between field and CC and the farmer can still drop resources without walking. Leaving such a gap might allow more fields to be placed. Hang In games, we often see players put field snapping at the corner of CC. This is not ideal, because farmers will have a walk a bit to drop resources. We name this case "hanging" entirely outside of CC. If we now shift that field a little inward toward the CC, it is still hanging, but only part of it is hanging. Then farmers can farm in the part where the field is not hanging, and they can drop resources without walking. That non-hanging part is around 8m. Now to state our problem more precisely, we want to place maximum number of fields around CC, allowing gap between CC, but keep certain non-hanging part. We disallow rotation. Although rotation might give better arrangement, the problem will become too difficult. In fact, disallowing rotation is the sole assumption of our algorithm. Under such assumption, our algorithm gives optimal placement. I also claim that if we allow rotation, no efficient algorithm exists. People who are familiar with algorithm, especially computational geometry, should realise this is a very difficult problem. This is shape arrangement in continuous 2D space, and deterministic algorithm might not even exist. Scientists usually do heuristics to find good-enough (but not optimal) solution in these problems. I had also been working on heuristics, but as I keep improving my heuristics, I found that our problem is quite special and is much simplified. It turned out that we can work out a combinatorial algorithm to really find the optimal placement. We basically do trapezoidal decomposition of the region, that we do sweep line algorithm over all such trapeziums, exhaust all combinations, and merge linearly related constraints. The algorithm is super complicated, but I think I made it. Do you like it?

See also this thread: https://wildfiregames.com/forum/topic/25280-black-powder-test/

Hi guys I am a blender hobbyist I would like to help with some models where should i start?