Amorphous Fortress: Exploring Emergent Behavior and Complexity in Multi-Agent 0-Player Games

We introduce the Amorphous Fortress-an abstract, open-ended artificial life simulation framework. In this system, entities are represented as finite-state machines (FSMs) which allow for multi-agent interaction within a constrained space. These agents are created by randomly generating and evolving the FSMs; sampling from pre-defined states and transitions. This environment was designed to explore the emergent AI behaviors found implicitly in simulation games such as Dwarf Fortress or The Sims. We apply two evolutionary algorithms to this environment, hill-climber and MAP-Elites, to explore the various levels of depth and interaction from the generated FSMs and to generate diverse sets of environments that exhibit dynamics estimated to be complex by analyses of agents' FSM architecture and activation. This paper combines the work of two previous non-archival workshop papers.