@article{Robison_Viglione_Zubek_Horswill_2021, title={AI Design Lessons for Social Modeling at Scale}, volume={17}, url={https://ojs.aaai.org/index.php/AIIDE/article/view/18911}, DOI={10.1609/aiide.v17i1.18911}, abstractNote={City of Gangsters is a commercial strategy game in which the player is principally challenged by navigating a complex and large-scale social network, in which every action resonates through the network and holds associated risks and rewards. Our procedurally-generated city results in a large social network with randomized and non-prescriptive configurations. Gameplay is oriented around social reciprocity and engaging in the same via an understanding of a concise set of social norms. Addressing these problems in a video game required a close unity between AI design and game design. We present four key AI design and implementation lessons learned in developing and shipping this game: the paramount need to make social actions and their consequences legible, the need for reversible actions, the need for modeled social norms to comprise a succinct set, and the need for individuals to be fungible with one another vis-a-vis social actions. We conclude with a description of the design affordances of this approach.}, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment}, author={Robison, Ethan and Viglione, Matthew and Zubek, Robert and Horswill, Ian}, year={2021}, month={Oct.}, pages={213-219} }