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SUMMARY:How humans build models of the world through temporal contingencie
 s - Prof Danielle Bassett
DTSTART:20201201T150000Z
DTEND:20201201T160000Z
UID:TALK153823@talks.cam.ac.uk
CONTACT:Sarah Morgan
DESCRIPTION:Human learners acquire not only disconnected bits of informati
 on\, but complex interconnected networks of relational knowledge. The capa
 city for such learning naturally depends on the architecture of the knowle
 dge network itself. I will describe recent work assessing network constrai
 nts on the learnability of relational knowledge\, and a free energy model 
 that offers an explanation for such constraints. I will then broaden the d
 iscussion to the generic manner in which humans communicate using systems 
 of interconnected stimuli or concepts\, from language and music\, to liter
 ature and science. I will describe an analytical framework to study the in
 formation generated by a system as perceived by a biased human observer\, 
 and provide experimental evidence that this perceived information depends 
 critically on a system's network topology. Applying the framework to sever
 al real networks\, we find that they communicate a large amount of informa
 tion (having high entropy) and do so efficiently (maintaining low divergen
 ce from human expectations). Moreover\, we also find that such efficient c
 ommunication arises in networks that are simultaneously heterogeneous\, wi
 th high-degree hubs\, and clustered\, with tightly-connected modules -- th
 e two defining features of hierarchical organization. Together\, these res
 ults suggest that many real networks are constrained by the pressures of i
 nformation transmission to biased human observers\, and that these pressur
 es select for specific structural features.
LOCATION:Online
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