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Talk
in
Workshop: 1st Workshop on Language in Reinforcement Learning (LaReL)

Invited Talk: Alison Gopnik

Nantas Nardelli


Abstract:

Understanding, learning and reasoning with abstract relations, like same and different or bigger and smaller, is challenging. We show that in an RL like causal learning task, very young children, 18-30 month olds, can learn both same and different relations and the functions becoming bigger and becoming smaller, generalize those relations to brand new and perceptually different objects, and use them to solve novel tasks. We suggest that both abstract causal representations, similar to causal graphical models, and early language may support this knowledge and learning.

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