Building Machines That Learn and Think Like People

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Test of the comprehension of the paper "Building Machines That Learn and Think Like People" authored by M. Lake, T. D. Ullman, J. B. Tenenbaum, and S. J. Gershman. doi: 10.1017/S0140525X16001837.

Student pseudonym (from https://courses.cs.ut.ee/2022/neuroseminar/spring --> your name on the right --> my data --> the table contains a pseudonym for each course) *

Which are examples of intuitive components humans seem to learn early and fast? *

1 point

persistence of objects

continuity of objects

solidity of objects

animate agens have goals

Required

Where did the article focus on? *

1 point

making models learn more with less constraints and less inductive biases

learn more causal models of the world

the importance of pattern recognition

the importance of other paradigms besides connectionist artificial neural networks

Required

Which was among the proposed hopeful future directions? *

1 point

selective attention

augmented working memory

prediction replay

first and second

second and third

If I have published the following articles, with corresponding citations. what is my h-index: Article 1, 50 citations, Article 2, 25 citations, Article 3 10 citations, Article 4, 0 citations, Article 5, 0 citations. *

1 point

28.3

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