Interacting with a system is key to uncovering its causal structure. A computational framework for interventional causal learning has been developed over the last decade, but how real causal learners might achieve or approximate the computations entailed by this framework is still poorly understood. Here we describe an interactive computer task in…

Proposes causal field theory as a model of causal reasoning. Suggests that anomaly detection through comparison with natural events triggers causal reasoning. This anomaly is interpreted in terms of agency; therefore, natural phenomena can be understood through an appeal to agency. The mechanism proposed never changes with development, whereas…