BEGIN:VCALENDAR
PRODID:-//github.com/ical-org/ical.net//NONSGML ical.net 4.0//EN
VERSION:2.0
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:STANDARD
DTSTART:20241103T020000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20250309T020000
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
DESCRIPTION:Note: BIS 526 students are required to attend in person. Other
 s are invited to attend in person but may also attend via zoom. Speaker- 
 Susan A. Murphy\, Ph\,D. Title- "Reinforcement Learning for Digital Healt
 h Interventions in the Dyadic Setting" Abstract We present our ongoing wo
 rk on the development of an online reinforcement learning (RL) algorithm 
 for dyadic digital intervention settings in which the task for the RL alg
 orithm is to assist the target person with a difficult illness be adheren
 t to behavioral activities. To achieve this goal the RL algorithm will no
 t only deliver digital interventions to the target person but also delive
 r interventions to assist the care partner to manage caregiving burden an
 d help the two individuals improve their relationship. That is\, differen
 t RL components target different elements of the dyad. The RL algorithm i
 s a multi-agent RL algorithm in which the 3 agents make decisions on the 
 3 elements of the dyad. We incorporate domain knowledge in the form of ap
 proximal causal directed acyclic graphs to speed up online learning in th
 is sparse data setting. This work is motivated by our development of the 
 ADAPTS-HCT multi-agent RL algorithm\, designed to improve medication adhe
 rence by young adults who have undergone a blood and bone marrow transpla
 nt. The RL algorithm will be deployed in summer 2026.\n\nAdmission:\nFree
 \n\nDetails URL:\nhttps://medicine.yale.edu/event/ysph-biostatistics-semi
 nar-6/\n
DTEND;TZID=America/New_York:20260217T130000
DTSTAMP:20260419T043813Z
DTSTART;TZID=America/New_York:20260217T120000
GEO:41.302961;-72.931638
LOCATION:106 A&B\, 47 College Street\, New Haven\, CT\, United States
SEQUENCE:0
STATUS:Confirmed
SUMMARY:YSPH Biostatistics Seminar-"Reinforcement Learning for Digital Hea
 lth Interventions in the Dyadic  Setting"
UID:dc797eec-6879-48f3-b0c2-e4dc6364f375
END:VEVENT
END:VCALENDAR