  Corvids, apes, and children solve The Crow and The Pitcher task (from Aesop's
Fables) indicating a causal understanding of the task. By cumulatively
interacting with different objects, how can cognitive agents abstract the
underlying cause-effect relations to predict affordances of novel objects? We
address this question by re-enacting the Aesop's Fable task on a robot and
present a) a brain-guided neural model of semantic-episodic memory; with b)
four task-agnostic learning rules that compare expectations from recalled past
episodes with the current scenario to progressively extract the hidden causal
relations. The ensuing robot behaviours illustrate causal learning; and
predictions for novel objects converge to Archimedes' principle, independent of
both the objects explored during learning and the order of their cumulative
exploration.
