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Doty, David; Eftekhari, Mahsa; Gasieniec, Leszek; Severson, Eric; Uznanski, Przemyslaw; Stachowiak, Grzegorz (, 62nd Annual IEEE Symposium on Foundations of Computer Science)
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Doty, David; Eftekhari, Mahsa; Gąsieniec, Leszek; Severson, Eric; Stachowiak, Grzegorz; Uznański, Przemyslaw (, Proceedings of the 40th ACM Symposium on Principles of Distributed Computing)
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Amir, Talley; Aspnes, James; Doty, David; Eftekhari, Mahsa; Severson, Eric E. (, 34th International Symposium on Distributed Computing, DISC 2020, October 12-16, 2020, Virtual Conference)Attiya, Hagit (Ed.)The standard population protocol model assumes that when two agents interact, each observes the entire state of the other agent. We initiate the study of the message complexity for population protocols, where the state of an agent is divided into an externally-visible message and an internal component, where only the message can be observed by the other agent in an interaction. We consider the case of O(1) message complexity. When time is unrestricted, we obtain an exact characterization of the stably computable predicates based on the number of internal states s(n): If s(n) = o(n) then the protocol computes a semilinear predicate (unlike the original model, which can compute non-semilinear predicates with s(n) = O(log n)), and otherwise it computes a predicate decidable by a nondeterministic O(n log s(n))-space-bounded Turing machine. We then consider time complexity, introducing novel O(polylog(n)) expected time protocols for junta/leader election and general purpose broadcast correct with high probability, and approximate and exact population size counting correct with probability 1. Finally, we show that the main constraint on the power of bounded-message-size protocols is the size of the internal states: with unbounded internal states, any computable function can be computed with probability 1 in the limit by a protocol that uses only one-bit messages.more » « less
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Doty, David; Eftekhari, Mahsa (, Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing)
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