Baritone AI pathfinder

Baritone AI pathfinder

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Can Baritone break temporary blocks

xBRUHHY opened this issue ยท 6 comments

commented

What do you need help with?

When using #build and other features, Baritone can place temporary blocks if allowPlace is enabled, but is there a way to make baritone break the blocks after using them?

Final checklist

  • I know how to properly use check boxes
  • I have not used any OwO's or UwU's in this issue.
commented

No, right now there is no way for Bariton to behave like you asked, and I don't think Bariton will ever be able to behave like that, because if Bariton for example places 1 block in front of it and then uses that block to do a parkour jump (say 4 blocks wide), then there is no way to go back and destroy that temporary block (ok, breaking it while flying through the air might be possible, but I don't know, that sounds very impractical).

commented

theres something called mlg

commented

Yes, I am aware of mlgs. Mlgs, short for Major League Gaming, describe the act of placing a water bucket right before hitting the ground in order to prevent fall damage. What I don't know is how they relate to your question. Could you explain yourself in further detail?

commented

you said there way no way to go back

commented

Yeah, that's correct but I still don't get what mlgs have to do with breaking blocks.

commented

I think the problem of MLGs and long parkour jumps (which Baritone can't do anyway) can be avoided by making the option incompatible with allowPlace some setting for those movements, just like backfill is incompatible with allowBreak allowParkour.

Theoretically (don't think it is likely to happen) it would also be possible to disallow doing those movements starting on a scaffolding block. Placing the block is independent of the movement used to reach the position so it should not break the invariant of movements only being dependent on the position they start from. (Unless I'm wrong) it also does not break other invariants so it can be done without breaking optimality.