Learning Macromanagement in StarCraft from Replays using Deep Learning — Neural networks are trained on 789,571 state-action pairs extracted from 2,005 replays of highly skilled players, achieving top-1 and top-3 error rates of 54.6% and 22.9% in predicting the next build action. By integrating the trained network into UAlbertaBot, an open source StarCraft bot, the system can significantly outperform the game’s built-in Terran bot and play competitively against UAlbertaBot with a fixed rush strategy. (via Mark Riedl)
Making Engineering Team Communication Clearer, Faster, Better — it’s very important to make sure you have a process that actually gets people to read the document. The write-only document fired off into the void is a common problem, and this talks about how to solve it (for design documents, but the principles translate).