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SUMMARY:Control theory for collective behaviour in the presence of a disea
 se - Matthew Turner (University of Warwick)
DTSTART:20230801T090000Z
DTEND:20230801T100000Z
UID:TALK203602@talks.cam.ac.uk
DESCRIPTION:Control theory is an important technique with which to underst
 and the behaviour of information processing agents. We study rational deci
 sion making for agents that face the possibility of infection with an SIR-
 type disease. Infection carries a cost\, encoded in objective function. Ag
 ents can modify their behaviour (infectivity) to exert some control\, but 
 this also carries a cost. We investigate how the optimal behavioiur\,&nbsp
 \; maximising an objective function\, depends on the cost of infectuon\, w
 hether the agents are selfish or utilitarian\, with nonlinear infection co
 sts to mimic health care capacity limits and uncertain vaccination develop
 ment times. We introduce another layer of control at the government level 
 with an objective function that may or may not be aligned with the populat
 ion and study the coupled control theory problem to establish optimal poli
 cy. We find a sharp switch in policy roughly equivalent to "lockdown" and 
 "herd immunity" strategies at a crtitical infection cost. Finally we formu
 late a form of physics inspired machine learning to attack the inverse pro
 blem of inferring the objective function of selfish agents from their beha
 viour.&nbsp\; This work is joint work together with Prof Ryoichi Yamamoto 
 (Kyoto Univ)\, Dr John Molina (Kyoto Univ) and Dr Simon Schnyder (Tokyo Un
 iv).
LOCATION:Seminar Room 2\, Newton Institute
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