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13 results for “public goods game”
Group size effects and critical mass in public goods games
<pre>This dataset accompanies the paper "Group size effects and critical mass in public goods games", https://doi.org/10.1038/s41598-019-41988-3 It records participant decisions in a set of binary one-shot Public Goods Games with curvilinear payoff function (see details in the paper). The explanation of the data fields is present also in the metadata of the file: # Cooperation: 0=defection, 1=cooperation, 99=the participant did not make the decision # Group: interacting group size (N) # Treatment: Critical Mass Nc # dropout: 1=the participant did not make the decision, 0=the participant made the decision # incompleted: 1=participant did not make all the decisions of the experiment; 0=participant did made all the decisions of the experiment # female: 1=female, 0=male </pre> <p> </p>
Large scale and information effects on cooperation in public good games
<pre>This dataset accompanies the paper "Large scale and information effects on cooperation in public good games", https://doi.org/10.1038/s41598-019-50964-w It records participant decisions in a set of Public Goods Games (see details in the paper). Explanation of the data fields: #participant_id: identification number for each participant in each treatment #player_alive: (for each round) 1=participant is still playing; 0=participant has been banned for forgetting three decisions or did not show up the first day. #group_avg_contribution: Average contribution #player_contribution: participant individual contribution to the PGG #round_number: round number #gender #age #treatment: see the publication for details regarding the different treatments # IBSEN metadata # 2017A2ECOCOOPANSA01ONL0000ESPMAD </pre>
The public goods game on multiplex networks
<p>The code and data used to create the figures in chapters 3-7 in the thesis "The public goods game on multiplex networks". The data is labelled for which figure it corresponds to.</p>
Supplementary data on learning about German farmers' willingness to cooperate from public goods games and expert predictions
<p>Supplemental files on learning about German farmers' willingness to cooperate from public goods games and expert predictions. </p>
Data and experiment files from: Payoff-based learning best explains the rate of decline in cooperation across 237 public-goods games
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Cooperation in public goods game does not require assortment and depends on population density
<p>The threshold public goods game is one of the best-known models of nonlinear public goods dilemmas. Cooperators and defectors typically coexist in this game when the population is assumed to follow the so-called structured deme model. In this paper we develop a dynamical model of a general N-player game in which there is no deme structure: individuals interact with randomly chosen neighbours and selection occurs between randomly chosen pairs of indi- viduals. We show that in the deterministic limit the dynamics in this model leads to the same replicator dynamics as in the structured deme model, i.e. coexistence of cooperators and defectors is typical in threshold public goods game even when the population is completely well-mixed. We extend the model to study the effect of density dependence and density fluctuation on the dynamics. We show analytically and numerically that decreasing population density increases the equilibrium frequency of cooperators till the fixation of this strategy, but below a critical density coop- erators abruptly disappear from the population. Our numerical investigations show that weak density fluctuations enhance cooperation, while strong fluctuations suppress it.</p>
Cooperation in public goods game does not require assortment and depends on population density
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Data and code for Fraser and Nettle, 'Hunger affects social decisions in a Public Goods Game but not an Ultimatum Game'
<p><strong>Data and code for Fraser and Nettle 'Hunger affects social decisions in a multi-round Public Goods Game but not a single-shot Ultimatum Game' </strong></p> <p>The attached R script reproduces all analyses in the paper. There are three .csv data files used by the script: the dataset for experiment 1, the main dataset for experiment 2, and the latency data for experiment 2.</p> <p>This version: April 2020.</p> <p>Since the version of October 2019, we switched the order of presentation of the experiments, so the one previously referred to as experiment 2 is now experiment 1 and vice versa. Other new analyses and sections have also been added.</p>
Data from: Evolution of conditional cooperation in public good games
<p class="Standard">It is observed that in a repeated public good game with same individuals, free riding by a few individuals in the initial rounds triggers free riding by others in the subsequent rounds. It is presumed that individuals tend to imitate social behaviour of successful or relatively high payoff individuals, irrespective of how the payoffs were obtained. However, humans are concerned about how the payoffs were obtained, such as whether the payoffs were obtained by cheating or good behaviour. Individuals are willing to incur certain cost in order to improve group benefits and these individuals gain prestige. In human societies individuals tend to imitate social behaviour of high prestige agents. We propose that when agents are aware of other agents' payoffs scores and their prestige, perhaps agents are more likely to imitate social behaviour of high prestige and high payoff agents. We introduce, population level affinity parameters such as affinity towards payoff and affinity towards prestige of role models. We show that, for certain affinity parameters, high levels of cooperation are established in a population consisting of heterogeneous conditional co-operators, when agents imitate social behaviour of high prestige and high payoff agents. The proposed model provides insights into why value-based societies are more successful than competitive societies in establishing cooperation.</p>
Data from: Payoff-based learning explains the decline in cooperation in public goods games
Economic games such as the public goods game are increasingly being used to measure social behaviours in humans and non-human primates. The results of such games have been used to argue that people are pro-social, and that humans are uniquely altruistic, willingly sacrificing their own welfare in order to benefit others. However, an alternative explanation for the empirical observations is that individuals are mistaken, but learn, during the game, how to improve their personal payoff. We test between these competing hypotheses, by comparing the explanatory power of different behavioural rules, in public goods games, where individuals are given different amounts of information. We find: (i) that individual behaviour is best explained by a learning rule that is trying to maximize personal income; (ii) that conditional cooperation disappears when the consequences of cooperation are made clearer; and (iii) that social preferences, if they exist, are more anti-social than pro-social.
Data from: Payoff-based learning explains the decline in cooperation in public goods games
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Data from: Evolution of conditional cooperation in public good games
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Data from: Group-size diversity in public goods games
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.