It was around 2010 before all the reinforcement learning madness :) It was a university student competition in (mostly computer science bachelor and master stu

It was around 2010 before all the reinforcement learning madness :) It was a university student competition in (mostly computer science bachelor and master students). The core algorithm is https://en.wikipedia.org/wiki/Expectiminimax https://en.wikipedia.org/wiki/Expectiminimax which is a type of heuristic tree search over the possible board states. Winning such a tournament meant you can write efficient C++ code (so you can search more states during the allocated turn) and you can invent/feature-engineer good heuristics that estimate how close is a board state to winning the game. I don't remember what heuristics was used, I don't even remember the rules :) But I've uploaded the source to github a few years ago: https://github.com/amitport/senet-ai https://github.com/amitport/senet-ai The heuristics are at: https://github.com/amitport/senet-ai/blob/master/SmartUtilit https://github.com/amitport/senet-ai/blob/master/SmartUtilit... I can't really make sense of it anymore :) but it seems to work