Dice Adventure: An Asymmetrical Collaborative Game for Exploring the Hybrid Teaming Effects

In this work, we designed and developed Dice Adventure, a turnbased multiplayer game where three characters work together to reach their individual goals and then a shared team goal to complete each level.Using Dice Adventure as the environment, we hosted a game competition with two tracks: agent and player.Participants could join one or both by submitting an agent they developed and/or signing up to play with the agents submitted by other developers.We collected competition game play data as part of a human-AI teaming pilot study to understand team behaviors, performance, and to test our systems.Insights from the competition also informed the design of a randomized controlled study for future experiments and competitions, aimed at exploring key human-AI teaming questions-such as how role assignments, team compositions, and team dynamics influence team performance.Our work introduces a novel gaming environment to support future research on human-AI teaming and offers preliminary insights into the design of such studies.