CausalCity: Simulated city aims to teach AI "counterfactual reasoning"

AI algorithms struggle to recognise events or objects in contexts that are different from the training set. A situation in the world is something that has no boundaries at all, you don't know what's in the situation, what's out of the situation.") If you're trying to train an AI to deal with this "unframed" world, you run into a lot of challenges. Humans learn about causal relationships by making interventions/actions in a given environment, observing the result, then refining the mental model they've "built" by making similar actions in subtly different environments in the great, fluid thing that is The World. It's hard to build AI training sets that can help algorithms "understand" the myriad causal relationships taking place at any given time in a similar way; rather than train them to understand more fixed patterns of behaviour: e.g. the hard numbers that need to be crunched to beat a human in a game of tightly circumscribed mathematical probabilities like chess.