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Social Learning in Multi Agent Multi Armed Bandits Abishek - PowerPoint PPT Presentation

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Social Learning in Multi Agent Multi Armed Bandits Abishek Sankararaman, UC Berkeley April 9, 2020 Joint Work with - Sanjay Shakkottai, Ronshee Chawla, UT Austin - Ayalvadi Ganesh, University of Bristol Multi Armed Bandit Problem A set of

  1. Social Learning in Multi Agent Multi Armed Bandits Abishek Sankararaman, UC Berkeley April 9, 2020 Joint Work with - Sanjay Shakkottai, Ronshee Chawla, UT Austin - Ayalvadi Ganesh, University of Bristol

  2. Multi Armed Bandit Problem A set of possible drugs with a-priori unknown cure rates

  3. Multi Armed Bandit Problem A set of possible drugs with a-priori unknown cure rates Task - Prescribe one of these to new incoming patients to both (i) cure them and (ii) collect data about their cure rates

  4. Multi Armed Bandit Problem A set of possible drugs with a-priori unknown cure rates Task - Prescribe one of these to new incoming patients to both (i) cure them and (ii) collect data about their cure rates Explore/Exploit Tradeo ff for each new patient [Thompson’ 33] Prescribe a drug that has shown the best promise so far Exploit Explore Try a new drug to discover more promising alternatives Run a risk of not curing these patients

  5. Outline 1. Single Agent MAB 2. The Multi-Agent Setup 3. The Gossiping Insert-Eliminate (Gosine) Algorithm 4. Insights

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