Starcraft AI blog

In January I wrote about the idea of an RPS analyzer that tries to predict the opponent’s strategy rock-paper-scissors style, picking up patterns in the sequence of opening tries. For example, many bots never vary a winning build until it loses, and some of those cycle through their choices in a fixed order. If successful, an RPS analyzer could improve the odds of predicting the opponent’s strategy from the get-go, so that Steamhammer could start its counter before it got scouting information to verify. At the time, I wasn’t sure whether an RPS analyzer would be a good idea.

I still think that an RPS analyzer is useless in the limit of very strong bots: PerfectBot will follow game theory and have exactly the right amount of randomness in its choices, and a pattern detector will detect nothing helpful. But as I prepare Steamhammer for AIIDE 2020 I have been playing over many games, and I’ve become convinced that most current learning bots follow predictable or partially predictable patterns that can be exploited.

The current release version of Steamhammer pays limited attention to its predictions, which are accurate only in simple cases. It deliberately shifts its attention over time from openings that counter the specific predicted enemy play toward openings which counter the opponent’s range of play. The changes to make it pay close attention to accurate predictions are easy, though. And there are easy-to-implement algorithms to detect patterns and return a prediction with its confidence level. Do you think it can be ready in time for the AIIDE deadline at the end of the month?