Imagine playing a game where you and your teammates have to work together to defeat an army of alien invaders. As you gain experience, you notice that each player starts to adopt a specific role and can predict what actions are needed without even communicating. This fascinating study explored collaborative skill acquisition using the game Co-op Space Fortress. The researchers developed a sophisticated model that mimics how humans learn to collaborate, incorporating reinforcement learning, motion extrapolation, and predictive processes. By understanding the complex cognitive processes involved in collaborative skill acquisition, we can apply these insights to improve teamwork in various fields. If you want to delve into this groundbreaking research on teamwork and cognitive architecture, check out the full article through the link below!

Abstract
We studied collaborative skill acquisition in a dynamic setting with the game Co-op Space Fortress. While gaining expertise, the majority of subjects became increasingly consistent in the role they adopted without being able to communicate. Moreover, they acted in anticipation of the future task state. We constructed a collaborative skill acquisition model in the cognitive architecture ACT-R that reproduced subject skill acquisition trajectory. It modeled role adoption through reinforcement learning and predictive processes through motion extrapolation and learned relevant control parameters using both a reinforcement learning procedure and a new to ACT-R supervised learning procedure. This is the first integrated cognitive model of collaborative skill acquisition and, as such, gives us valuable insights into the multiple cognitive processes that are involved in learning to collaborate.

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