Reasoning about causality in games

Causal reasoning and game-theoretic reasoning are fundamental topics in artificial intelligence, among many other disciplines: this paper is concerned with their intersection. Despite their importance, a formal framework that supports both these forms of reasoning has, until now, been lacking. We offer a solution in the form of (structural) causal games, which can be seen as extending Pearl's causal hierarchy to the game-theoretic domain, or as extending Koller and Milch's multi-agent influence diagrams to the causal domain. We then consider three key questions: How can the (causal) dependencies in games – either between variables, or between strategies – be modelled in a uniform, principled manner? How may causal queries be computed in causal games, and what assumptions does this require? How do causal games compare to existing formalisms?