Towards human-like artificial intelligence using StarCraft 2
Henrik Siljebråt, Caspar Addyman, Alan D. Pickering · 2018
On our path towards artificial general intelligence, video games have become excellent tools for research. Reinforcement learning (RL) algorithms are particularly successful in this domain, with the added benefit of having fairly well established biological foundations. To improve how artificial intelligence research and the cognitive sciences can inform each other, we argue the StarCraft II Learning Environment is an ideal candidate for an environment where humans and artificial agents can be tested on the same tasks. We present an upcoming study using this environment, where the goal is to investigate how RL can be extended to enable abstract human abilities such as moments of insight. We claim this is valuable for advancing our understanding of both artificial and natural intelligence, thereby leading to improved models of player behaviour and for general video game playing.