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.
- Pub Date:
- February 2020
- Computer Science - Artificial Intelligence;
- Computer Science - Robotics;
- To appear in ICLR 2020 4 pages For associated videos, see https://www.youtube.com/playlist?list=PLIfoHEM1gr24EniCzBuUxZ2tqNpQA8QQm