Evidence map›Paper›PMID 41719357›Full record

ArticlePLoS computational biology2026

Coevolutionary dynamics of cooperation, risk, and cost in collective risk games.

Lichen Wang, Shijia Hua, Yuyuan Liu, Liang Zhang, Linjie Liu, Attila Szolnoki

Abstract read
In one paragraph

Article in PLoS computational biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lichen WangCollege of Science, Northwest A & F University, Yangling, Shaanxi, China.
Shijia HuaCollege of Science, Northwest A & F University, Yangling, Shaanxi, China.
Yuyuan LiuCollege of Science, Northwest A & F University, Yangling, Shaanxi, China.ORCID https://orcid.org/0009-0003-4681-582X
Liang ZhangCollege of Science, Northwest A & F University, Yangling, Shaanxi, China.
Linjie LiuCollege of Science, Northwest A & F University, Yangling, Shaanxi, China.ORCID https://orcid.org/0000-0003-0286-8885
Attila SzolnokiInstitute of Technical Physics and Materials Science, Centre for Energy Research, Budapest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Addressing both natural and societal challenges requires collective cooperation. Studies on collective-risk social dilemmas have shown that individual decisions are influenced by the perceived risk of collective failure. However, existing feedback-evolving game models often focus on a single feedback mechanism, such as the coupling between cooperation and risk or between cooperation and cost. In many real-world scenarios, however, the level of cooperation, the cost of cooperating, and the collective risk are dynamically interlinked. Here, we present an evolutionary game model that considers the interplay of these three variables. Our analysis shows that the worst-case scenario, characterized by full defection, maximum risk, and the highest cost of cooperation, remains a stable evolutionary attractor. Nevertheless, cooperation can emerge and persist because the system also supports stable equilibria with non-zero cooperation. The system exhibits multistability, meaning that different initial conditions lead to either sustained cooperation or a tragedy of the commons. These findings highlight that initial levels of cooperation, cost, and risk collectively determine whether a population can avert a tragic outcome.

Indexed as

Biological EvolutionCooperative BehaviorGame TheoryComputational BiologyComputer SimulationHumansRisk

Identifiers

PMID41719357
PMCPMC12923141

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.