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Early work on disciplinary-integrated games (DIGs) focused on Cartesian time-series analyses as the formal representations through which the game communicates challenges and opportunities to the players as well as the formal representations through which the players control the game. In our earlier work, we explored the potential generalizability of the DIG genre in terms of hypothetical examples in physics, biology, chemistry, and the social sciences as well as in terms of multiple model types including constraint-system analyses, system dynamics models, situation-action models, and agent-based models. In particular, Sengupta and Clark and Krinks, Sengupta, and Clark explored the integration of computational modeling, physical models, and Cartesian models. Building on that work, we began outlining theoretical frameworks and arguments highlighting the affordances of moving DIG design more deeply into agent-based modeling. In the current paper, we present the actual design process and rationale through which we developed prototypes of two multiplayer DIG prototypes with agent-based models as the mode of control wherein players create, trade, and elaborate on one another’s code as part of gameplay. We close with a discussion of implications for the design of disciplinary-integrated games leveraging agent-based modeling as the focal formal representation for communication and control.

Multiplayer Disciplinarily-Integrated Agent-Based Games: SURGE Gameblox