...
首页> 外文期刊>Applied mathematics and computation >A mathematical model for the climate change: Can unpredictability offset the temptations to pollute?
【24h】

A mathematical model for the climate change: Can unpredictability offset the temptations to pollute?

机译:气候变化的数学模型:不可预测性可以抵消污染的诱惑吗?

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

The climate change is an example of the biggest social dilemma in the human history. Climate change mitigation can be successful only if the whole world will undertake an internationally coordinated collective action. Costs to reduce emissions of greenhouse gases can be easily calculated for each individual, but benefits of the successful reduction will be distributed among all the "players", independently from theft actual contributions to sustainable development. Evolutionary games provide a suitable theoretical framework for studying the challenges of climate change, and we will build on this fact in the present paper to study the evolution of cooperation and discuss its implications for offsetting the temptations to pollute. It has namely become painfully clear that tackling the climate change will be costly, and accordingly, the temptations to pollute will always be present. Can the element of unpredictability that is inherently present in social interactions and the environment increase the probability of adopting the cleaner strategy? We employ the spatial prisoner's dilemma game where the cooperative behaviour is challenged by defection that promises individuals a higher fitness and is thus more likely to prevail. Obtained results are contrasted with real data and indicators of climate change. (C) 2015 Elsevier Inc. All rights reserved.
机译:气候变化是人类历史上最大的社会困境的一个例子。只有全世界都将采取国际协调的集体行动,缓解气候变化的努力才能成功。可以很容易地为每个人计算减少温室气体排放的成本,但是成功减少排放的收益将分配给所有“参与者”,而与盗窃对可持续发展的实际贡献无关。进化博弈为研究气候变化的挑战提供了一个合适的理论框架,我们将在本文中以此为基础来研究合作的演变并讨论其对抵消污染诱惑的影响。痛苦地清楚地表明,应对气候变化将付出高昂的代价,因此,总是存在污染的诱惑。社会互动和环境中固有的不可预测因素能否增加采用更清洁策略的可能性?我们使用空间囚徒困境游戏,其中合作行为受到叛逃的挑战,叛逃使个人有更高的适应能力,因此更有可能获胜。将获得的结果与实际数据和气候变化指标进行对比。 (C)2015 Elsevier Inc.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号