Applying causal inference to understand emergent behavior

Emergent behaviors in simulations require explanation, so that valid behaviors can be separated from design or coding errors. Validation of emergent behavior requires accumulation of insight into the behavior and the conditions under which it arises. Previously, we have introduced an approach, Explanation Exploration (EE), to gather insight into emergent behaviors using semi-automatic model adaptation. We improve our previous work by iteratively applying causal inference procedures to samples gathered from the semi-automatic model adaptation. Iterative application of causal inference procedures reveals the interactions of identified abstractions within the model that cause the emergent behavior. Uncovering these interactions gives the subject matter expert new insight into the emergent behavior and facilitates the validation process.