Conjecture—Systematic generalization via rule learning as an inductive bias

Establish whether encoding systematic generalization through learned compositional rules is an effective inductive bias for embodied agents to achieve robustness to variations in tasks and environments.

Background

Embodied agents must generalize beyond limited, non-IID training data in changing environments. Systematic generalization—learning rules for composing concepts—may provide a powerful inductive bias.

The authors conjecture that encouraging learning of general rules can enable robust performance across task and environment variations.