Models as games: a novel approach for 'gamesourcing' parameter data and communicating complex models
Models as games: a novel approach for 'gamesourcing' parameter data and communicating complex models
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模型作为游戏：一种用于“游戏采购”参数数据和通信复杂模型的新颖方法
DOI：
10.1101/2021.09.23.461497
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Minderman J
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文献类型：
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作者：
Minderman J
1概述由于人类栖息地丧失和自然资源开发，生物多样性日益迅速地丧失，模型已成为保护科学中不可或缺的工具。除了它们的生态成分之外，在这样的模型中准确地表示人类决策过程对于最大化它们的效用至关重要。随着建模复杂性的增加，这可能会带来问题，这使得它们在通信和参数方面具有挑战性。游戏被用作科学交流工具的历史由来已久，但作为数据收集工具的使用较少，特别是在视频游戏形式。我们提出了一种新的方法来(1)帮助复杂的社会-生态模型的交流，(2)通过显式地将现有的建模框架转换为交互式视频游戏来提供“游戏源”人类决策数据。我们向玩家呈现了一个自然资源管理游戏作为社会-生态建模框架(通用管理策略评估)的前端。玩家的行动取代了对野生动物种群做出管理决策的模型算法，野生动物以农作物为食，因此可能会降低农业产量。许多非玩家代理人(农民)通过模型化的算法对玩家的管理做出反应，采取可能影响他们的作物产量和动物种群的行动。玩家被要求设定自己的管理目标(例如，将动物数量保持在一定水平或提高产量)，并做出相应的决定。我们还要求试验玩家提供关于游戏玩法和目的的任何反馈。我们通过收集和分析来自试验玩的样本的游戏数据来展示这种方法的有效性，在该样本中，我们系统地改变了两个模型参数，并允许试验玩家通过游戏界面与模型交互。作为说明，我们展示了土地所有权和系统中农民数量的变化如何影响决策模式以及人口轨迹(灭绝概率)。我们根据收到的试验者反馈讨论了这种模型博弈方法的潜力和局限性。特别是，我们强调了对游戏框架的共同担忧(感觉到缺乏“现实主义”或与特定背景的相关性)实际上是对基本模型的批评，而不是游戏本身。这进一步突出了游戏和模型之间的相似之处，以及模型游戏在帮助交流复杂模型方面的效用。我们的结论是，视频游戏可能是保护和自然资源管理的有效工具，尽管它们提供了一种有希望的手段来收集关于人类决策的数据，但在这样做时仔细考虑外部有效性和潜在的偏见是至关重要的。
1SummaryModels have become indispensable tools in conservation science in the face of increasingly rapid loss of biodiversity through anthropogenic habitat loss and natural resource exploitation. In addition to their ecological components, accurately representing human decision-making processes in such models is vital to maximise their utility. This can be problematic as modelling complexity increases, making them challenging to communicate and parameterise.Games have a long history of being used as science communication tools, but are less widely used as data collection tools, particularly in videogame form. We propose a novel approach to (1) aid communication of complex social-ecological models, and (2) “gamesource” human decision-making data, by explicitly casting an existing modelling framework as an interactive videogame.We present players with a natural resource management game as a front-end to a social-ecological modelling framework (Generalised Management Strategy Evaluation, GMSE). Players’ actions replace a model algorithm making management decisions about a population of wild animals, which graze on crops and can thus lower agricultural yield. A number of non-player agents (farmers) respond through modelled algorithms to the player’s management, taking actions that may affect their crop yield as well as the animal population. Players are asked to set their own management goal (e.g. maintain the animal population at a certain level or improve yield) and make decisions accordingly. Trial players were also asked to provide any feedback on both gameplay and purpose.We demonstrate the utility of this approach by collecting and analysing game play data from a sample of trial plays, in which we systematically vary two model parameters, and allowing trial players to interact with the model through the game interface. As an illustration, we show how variations in land ownership and the number of farmers in the system affects decision-making patterns as well as population trajectories (extinction probabilities).We discuss the potential and limitations of this model-game approach in the light of trial player feedback received. In particular, we highlight how a common concern about the game framework (perceived lack of “realism” or relevance to a specific context) are actually criticisms of the underlying model, as opposed to the game itself. This further highlights both the parallels between games and models, as well as the utility of model-games to aid in communicating complex models. We conclude that videogames may be an effective tool for conservation and natural resource management, and that although they provide a promising means to collect data on human decision-making, it is vital to carefully consider both external validity and potential biases when doing so.