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TU Berlin

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Online Fair Division

Martin Aleksandrov (TU Berlin)


Online Fair Division is a framework that allows us to distribute resources to agents. Unlike its offline counterpart, the resources in Online Fair Division arrive over time and must be allocated immediately to agents. We propose a model for Online Fair Division and two randomized mechanisms for it: LIKE and BALANCED LIKE. We also adopt standard concepts from Offline Fair Division such as strategy-proofness, envy-freeness and Pareto efficiency to Online Fair Division, completely characterize these properties and show that LIKE and BALANCED LIKE mechanisms are the only mechanisms that satisfy some of these properties. Finally, we investigate their computational properties and conclude with a small experiment.


Martin Aleksandrov
TEL 512

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