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zenodo.org

Amiridis, V.1, Marinou, E.1, Hostetler, C.2, Koopman, R.3, Cecil, D., J.4, Moisseev, D.5, Tackett, J.2, Gross, S.6, Baars, H.7, Redemann, J.8, Marenco, F.9, Baldini, L.10, Tanelli, S.11, Fielding, M.12, Janisková, M.12, Tanaka, T.13, O’Connor, E.14, Fjæraa, A., M.15, and the ACPPV consortium 16   1Institute of Astronomy, Astrophysics, Space Applications & Remote Sensing (IAASARS), National Observatory of Athens (NOA), 15236 Athens, Greece 2NASA Langley Research Center, Hampton, United States 3European Space Research and Technology, European Space Agency (ESA/ESTEC), Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands 4NASA Marshall Space Flight Center, Earth Science Branch, 320 Sparkman Dr NW, AL 35805, Huntsville, United States 5Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki, Finland 6Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Weßling 82234, Germany 7Leibniz Institute for Tropospheric Research (TROPOS), Permoserstraße 15, 04318 Leipzig, Germany 8School of Meteorology, University of Oklahoma, Norman, Oklahoma, United States 9The Cyprus Institute, 20 Konstantinou Kavafi Street, 2121 Nicosia, Cyprus 10National Research Council, Insitute of Atmospheric Science and Climate (CNR-ISAC), Via Fosso del Cavaliere, 100, 00133, Roma, Italy 11Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States 12European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, United Kingdom 13Earth Observation Research Center, Japan Aerospace Exploration Agency (JAXA), Tsukuba, Ibaraki 305-8505, Japan 14Finnish Meteorological Institute, Climate Research Programme, Erik Palménin aukio 1, FI-00560, Helsinki, Finland 15Climate and Research Institute NILU, P.O. Box 100, 2027 Kjeller, Norway 16 57 institutes, universities, and space agencies   Aerosols, clouds, precipitation, and the processes governing their interactions are the grand challenges for cu

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arxiv.org

We perform a behavioral experiment of karma, a class of mechanisms for repeated resource allocation with attractive fairness and efficiency properties, in theory. Individuals in these mechanisms bid non-tradable credits that flow from resource consumers to yielders, like karma. Human subjects recruited on Amazon MTurk are repeatedly and randomly paired to bid karma according to time-varying and stochastic individual preferences or urgency to acquire resources. Treatments varied in the dynamic urgency process (frequent moderate urgency versus sporadic high urgency) and the richness of the bidding scheme (binary versus full range). Results are benchmarked against random allocation, and karma achieves a (almost) Pareto improvement over random, despite the MTurk subjects deviating significantly from the theoretically optimal Nash bidding policy. Maximum improvement is attained by subjects that deviate from Nash by up to one karma bid unit on average, and positive improvement is attained with average deviations of up to 3-4 bid units. These findings hold across all treatments, among which no significant differences are found, with the exception of the sporadic high urgency process with binary bidding treatment being (weakly) favorable over others. These results offer behaviorally robust lower bounds for the expected performance of karma in human populations. They also provide guidance for future testing and implementation of karma mechanisms in the real world.

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