In my last tafl post, I remarked that I’m nearing the end of my current OpenTafl sprint. Now, it’s wrapped up. Here’s what I finished:

1. Write about 70% of a new evaluation function. It’s designed to easily accommodate tweaks and modifications, which will undoubtedly be required as I learn more about the game and uncover positions that the current function evaluates incorrectly.
2. Move OpenTafl into its own repository, so I can publish the source.
3. Package and test OpenTafl for binary distribution.
4. Rewrite exploration to generate and sort moves prior to generating states.

All three of these are done, and OpenTafl downloads and source releases can be found at the Many Words Softworks site for OpenTafl. Play and enjoy. For questions, comments, or bug reports, please leave a comment, or drop me an email. (My contact information is in the About section at the main page.)

Here’s what’s on the list for the next sprint:

1. Support for easy position entry. This will require creating some sort of short-form positional notation, akin to FEN from the chess world.
2. External AI support, a la several chess engines. This will require defining a protocol by which OpenTafl can communicate with an external AI, including communicating things like the rules of the variant in question.
3. Partial time control, so that OpenTafl can be limited to a certain number of seconds per turn.
4. Some search improvements and tweaks. The prior three features are important stepping stones to this one; they’ll let me test OpenTafl against itself by quick-play tournaments, and therefore verify what sort of impact my changes are having.

As you can see, the next sprint is less about the nitty-gritty AI research and more about foundational work in developing OpenTafl as an engine for future AI research—my own and others. Ultimately, that’s a more important task.