Using co-evolved RTS opponents to teach spatial tactics

This paper describes a co-evolutionary algorithm for generating simple spatially oriented tactics and considers whether students can learn better by playing against co-evolved opponents or by playing against an expert system or other similar hard-coded opponent. Although a number of artificially intelligent tutoring and e-learning systems exist, our work looks at using co-evolution to generate competent opponents for human students to learn from. This paper describes and discusses early results on using computationally intelligent opponents for tactical training of human students. Initial results indicate that the learning environment for human players, measured by game difficulty and transfer of training, is comparable across co-evolved and hard-coded computer opponents.