Social simulation research seeks to understand the dynamics of complex human behavior by simulating populations of individual decision-makers as multi-agent systems. However, prior work in games and entertainment fail to account for interactions between social behavior, geography, and relationships in a manner that allows researchers to easily reuse their frameworks and model social characters. We present Anthology, an extensible software framework for modeling human social systems, within the context of an ongoing research agenda to integrate AI techniques from social simulation games and computational social science to enable researchers to model and reason about the complex dynamics of human social behavior. Anthology comprises a motive-based agent decision making algorithm; a knowledge representation system for relationships; a flexible specification language for precondition-effect-style actions; a user interface to inspect and interact with the simulation as it runs in real-time; and an extensive user documentation and reference manual. We describe our participatory research design process used for the developing Anthology, the state of the current system, it’s limitations and our future development directions.