Red Blob Games

IMO, to start with AI, it's best to start as simple as possible so that you understand the algorithms that drive things that are accessible to tweak. If you are a gamer, think about the various AI routines that control pathfinding, resource collection, and strategy for computer players in strategy games. Some of the concepts of BFS and DFS build into Minimax strategies and other types of "simple" approaches to searching decision spaces/states for optimal approaches to problem solving. This gets into the development of heuristics for approximating outcomes. All of this is fantastic baseline for understanding more complex AI and machine learning algorithms. While it's easy to jump into ML or AI at a higher level, without the baseline understanding of the search algorithms and probability landscapes that are underpinnings to advanced work in these fields, you'll probably never feel like you understand what is going on.

You can find some fun tutorials here: https://www.redblobgames.com

The CS 188 "Intro to AI" class at Berkeley is excellent: http://ai.berkeley.edu/home.html

It used to be on edx.org but I think a lawsuit about accessibility required them to remove it? Perhaps you can find it in the edX archives.

Edit: looks like you can find the lecture videos and other resources on the Berkeley site: http://ai.berkeley.edu/lecture_videos.html

Ah, redblobgames! I remember their hexagonal coordinate system post from many years ago:

https://www.redblobgames.com/grids/hexagons/

An excellent example of their more interactive posts and great for those interested in hex-grid rendering and navigating.

edit: wow, over 10 years ago and the content has been updated but the look and feel is much as I remember it. This was before reactive systems took over the web, too, so the 'toggle selection here, see updates everywhere' was quite notable for the time.

On the actual topic of the post.. I think flow fields easily get overshadowed by waypoints and other hierarchical approaches. Or, folded into the heuristic function for A*.

I think the follow up games to HOMAM3 suffered a lot from focus on graphics and looks, opposed to investing more time into gameplay, map design, and computer opponents. They lost a lot of charm. Skeptical, whether yet another 3D graphics title will reach the heights of HOMAM3. Just too much effort spent on unimportant stuff. Maybe hire some good 2D artists.

Big pet peeve also: A Heroes game without a hex grid battle field just feels wrong. Square logic is easier, but come on, get good developers and look at something like https://www.redblobgames.com/grids/hexagons/ and figure out the logic. It is not magic.

This year I've mostly been updating existing pages in small ways (examples: [1] [2]). This week I've been fixing broken links, which isn't a good HN submission.

I think the best candidate is https://www.redblobgames.com/making-of/draggable/ . It's from earlier this year and hasn't been posted to HN yet (I think).

[1] https://simblob.blogspot.com/2023/04/explaining-hexagon-layout-class.html
[2] https://simblob.blogspot.com/2023/04/improving-mapgen4s-boundaries-part-2.html

Planning to write blog post(s) about how i made the game, but basically the techniques i used are the following:

- 2D ray tracing visibility algorithm (spolight): https://www.redblobgames.com/articles/visibility/

- Simplex noise procedural maps: https://www.redblobgames.com/maps/terrain-from-noise/

- WebGL2 rendering

- Websockets with binary data

- Deno

- Hetzner dedicated servers

- Docker Swarm Mode