ROS as a Pearl Causal Model

From Pearl, Judea. The Book of Why (p. 13). Basic Books. Kindle Edition. The definition of “causation” is simple, if a little metaphorical: a variable X is a cause of Y if Y “listens” to X and determines its value in response to what it hears. Pearl develops a whole science of Causal modeling to answer questions of science. His view of AI involves computing answers to causal questions (e.g. Does the marble hitting the floor cause a sound or does the sound cause the marble to hit the floor?). ROS has a publish/subscribe model between programs (or sensors) that generate data and programs that "listen" to the data and act on the results. This is clearly a causal connection. While not mentioned in the book explicitly Pearl's view of causality fits the ROS model, forming an interesting way to think about robot control. I can highly recommend this book.