“Adaptative bots for real-time strategy game via map characterization” (A.Fernández-Ares, P.García-Sánchez, A.M. Mora, J.J Merelo) is the title of the paper we have presented in CIG2012. In this work we use Genetics Algorithms for improve an adaptative bot for play (and win!) to planet wars. We made it through the characterization of the maps, studing those features (calculated quickly) that influence in bot behavior:
This paper presents a proposal for a fast on-line map analysis for the RTS game Planet Wars in order to define specialized strategies for an autonomous bot. This analysis is used to tackle two constraints of the game, as featured in the Google AI Challenge 2010: the players cannot store any information from turn to turn, and there is a limited action time of just one second.They imply that the bot must analyze the game map quickly, to adapt its strategy during the game. Based in our previous work, in this paper we have evolved bots for different types of maps.
Then, all bots are combined in one, to choose the evolved strategy depending on the geographical configuration of the game in each
Several experiments have been conducted to test the new approach, which outperforms our previous version, based on an off-line general training.