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(3 edits) (+1)

Because of how much I enjoyed your entry last week, I had to play yours for this week, too. Props to you for going for a more ambitious project. I think you did a great job distilling Minecraft's sense of discovery, improvement, and achievement into a mini project.

I would have liked to see an exponential curve for upgrades. My whole playthrough I had been looking forward to absolutely destroying a 5x5 grid of blocks with a single click, and having my sight range expanded to like 50-100 blocks wide. (But then again, speed might then become a limiting factor, so maybe the equipment upgrades would need to implicitly upgrade speed). This to me is a more fitting way to reward the player and wouldn't have taken too much more effort; even a single tier at the very end of absolute godlike abilities would've sufficed!

Regardless, procedural terrain generation is no small feat to pull off within the time frame, and I commend you for that. What was your algorithm for ore clusters (maybe a pre-defined set of shapes with a set frequency per ore)? I'm assuming the caves were cellular automata?

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thank you for your kind words and advice! The generation was just different seeds of perlin noise to create ore clusters and caves, although a cellular automata approach would be interesting.

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Ah, I see. I never would have guessed the project's ores and caves had used the same process. Cellular automata for terrain generation was all the rage back in the day when I first got into game dev; nowadays, though, the hot thing seems to be so-called "wave function collapse." Of course, the latter might not be entirely relevant for this situation, I just wanted to mention it while we were on the topic in general. Love this stuff!

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I'm going to have to try something like that for one of my game jams soon! I love procedural generation, but it's so hard to implement in a game jam setting, so I was extremely impressed to see that.

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Not sure how hard it is to implement perlin noise procedural generation in other engines, but Python made it very easy with the perlin_noise library. Definitely a cool feature to implement during a short time constraint!