TY - JOUR
T1 - Causal generative models are just a start
AU - Davis, Ernest
AU - Marcus, Gary
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Human reasoning is richer than Lake et al. acknowledge, and the emphasis on theories of how images and scenes are synthesized is misleading. For example, the world knowledge used in vision presumably involves a combination of geometric, physical, and other knowledge, rather than just a causal theory of how the image was produced. In physical reasoning, a model can be a set of constraints rather than a physics engine. In intuitive psychology, many inferences proceed without detailed causal generative models. How humans reliably perform such inferences, often in the face of radically incomplete information, remains a mystery.
AB - Human reasoning is richer than Lake et al. acknowledge, and the emphasis on theories of how images and scenes are synthesized is misleading. For example, the world knowledge used in vision presumably involves a combination of geometric, physical, and other knowledge, rather than just a causal theory of how the image was produced. In physical reasoning, a model can be a set of constraints rather than a physics engine. In intuitive psychology, many inferences proceed without detailed causal generative models. How humans reliably perform such inferences, often in the face of radically incomplete information, remains a mystery.
UR - http://www.scopus.com/inward/record.url?scp=85062752140&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062752140&partnerID=8YFLogxK
U2 - 10.1017/S0140525X17000115
DO - 10.1017/S0140525X17000115
M3 - Comment/debate
C2 - 29342689
AN - SCOPUS:85062752140
SN - 0140-525X
VL - 40
SP - e262
JO - The Behavioral and brain sciences
JF - The Behavioral and brain sciences
ER -