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Learning to play public good games

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Alex J. Bladon, Tobias Galla

Physics and Society · Submitted 5 Jul 2011

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim In particular we show that coherent cycles may emerge driven by noise in the adaptation dynamics.

how it is stated · hedged possibility 0.65 read the record →

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arXiv ID1107.0878 (version 1)
Pith IDWVE22DY6, Pith's permanent record of this paper and its review
CitationAlex J. Bladon, Tobias Galla. "Learning to play public good games." arXiv:1107.0878 (2011). https://pith.science/paper/WVE22DY6
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The compiled record

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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,125 input tokens, $0.0002 reported.

What the abstract itself states, as probabilities: claims first 0.09 · states limitation 0.23 · human participants 0.09 · controlled comparison 0.04 · randomized assignment 0.01 · states quantitative result 0.06 · compares with prior results 0.88 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

We extend recent analyses of stochastic effects in game dynamical learning to cases of multi-player games, and to games defined on networked structures. By means of an expansion in the noise strength we consider the weak-noise limit, and present an analytical computation of spectral properties of fluctuations in multi-player public good games. This extends existing work on two-player games. In particular we show that coherent cycles may emerge driven by noise in the adaptation dynamics. These phenomena are not too dissimilar from cyclic strategy switching observed in experiments of behavioural game theory.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We extend recent analyses of stochastic effects in game dynamical learning to cases of multi-player games, and to games defined on networked structures. contribution 1.00 0.90 0.07 asserted 0.97
s1 By means of an expansion in the noise strength we consider the weak-noise limit, and present an analytical computation of spectral properties of fluctuations in multi-player public good games. method 0.84 0.94 0.14 asserted 0.99
s2 This extends existing work on two-player games. contribution 0.43 0.25 0.04 asserted 0.97
s3 In particular we show that coherent cycles may emerge driven by noise in the adaptation dynamics. result 1.00 0.93 0.53 hedged possibility 0.65
s4 These phenomena are not too dissimilar from cyclic strategy switching observed in experiments of behavioural game theory. interpretation 0.99 0.18 0.10 asserted 0.69

What kind of paper the classifier reports this is: theoretical result 1.00 · evidence from proof or derivation 1.00.

What was examined, and what was not

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  • full text
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  • references and citing sentences
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  • P abstract
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  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We extend recent analyses of stochastic effects in game dynamical learning to cases of multi-player games, and to games defined on networked structures. By means of an expansion in the noise strength we consider the weak-noise limit, and present an analytical computation of spectral properties of fluctuations in multi-player public good games. This extends existing work on two-player games. In particular we show that coherent cycles may emerge driven by noise in the adaptation dynamics. These phenomena are not too dissimilar from cyclic strategy switching observed in experiments of behavioural game theory.

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1 arXiv paper cite this in 3 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it · 1 sentence without a confident label

Cites it as background 1 paper

What it cites · 8 sentences without a confident label

Builds on 1 paper
  • Such stochastic effects have recently been studied for two-player games in [ref] , the main contribution of the current work is to extend these approaches to the case of multi-player games, and to games on networks.

    Cycles of cooperation and defection in imperfect learning · Conclusion and outlook · 0.88

Compares with 1 paper
  • Eq. ([ref]) differs from the two player-case studied in [ref] where the correlations of the noise associated with strategies belonging to different players is zero.

    Cycles of cooperation and defection in imperfect learning · Batch-size expansion for a well-mixed, three-player game · 0.96

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