Seminar by Srinivas Arigapudi (IIT Kanpur)

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Venue:  Amex Room

Abstract:-
 We study coordination in multi-population environments where agents revise actions after observing finite independent samples of others’ behavior and applying deterministic monotone decision rules. The framework covers a broad class of commonly studied learning dynamics, and it allows heterogeneity across populations. Except for the knife-edge case in which every population simply copies one sampled action, coordination is globally stable: almost every trajectory converges to a coordinated state in which everyone chooses the same action. The proof connects monotone sampling rules to reliability functions of coherent systems. We show that relaxing independence, monotonicity, or within-population homogeneity can generate stable miscoordination.

All are cordially invited.

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