MacLeod Miles, Nersessian Nancy J
Department of Philosophy, University of Twente, Drienerlolaan 5, 7522 NB, Enschede, the Netherlands.
Department of Psychology Harvard University, 33 Kirkland St, Cambridge, MA, 02138, USA.
Stud Hist Philos Biol Biomed Sci. 2019 Dec;78:101201. doi: 10.1016/j.shpsc.2019.101201. Epub 2019 Aug 14.
In this paper we aim to give an analysis and cognitive rationalization of a common practice or strategy of modeling in systems biology known as a middle-out modeling strategy. The strategy in the cases we look at is facilitated through the construction of what can be called mesoscopic models. Many models built in computational systems biology are mesoscopic (midsize) in scale. Such models lack the sufficient fidelity to serve as robust predictors of the behaviors of complex biological systems, one of the signature goals of the field. This puts some pressure on the field to provide reasons for why and how these practices are warranted despite not meeting the stated goals of the field. Using the results of ethnographic study of problem-solving practices in systems biology, we aim to examine the middle-out strategy and mesoscopic modeling in detail and to show that these practices are rational responses to complex problem solving tasks on cognitive grounds in particular. However making this claim requires us to update the standard notion of bounded rationality to take account of how human cognition is coupled to computation in these contexts. Our account fleshes out the idea that has been raised by some philosophers on the "hybrid" nature of computational modeling and simulation. What we call "coupling" both extends modelers' capacities to handle complex systems, but also produces various cognitive and computational constraints which need to be taken into account in any computational problem solving strategy seeking to maintain insight and control over the models produced.
在本文中，我们旨在对系统生物学中一种常见的建模实践或策略——中间向外建模策略进行分析并给出认知合理性说明。我们所研究案例中的该策略是通过构建所谓的介观模型来实现的。计算系统生物学中构建的许多模型在规模上都是介观（中等大小）的。这类模型缺乏足够的保真度，无法作为复杂生物系统行为的可靠预测器，而这是该领域的标志性目标之一。这给该领域带来了一些压力，需要说明尽管这些实践未达到该领域既定目标，但为何以及如何是合理的。利用对系统生物学中问题解决实践的人种志研究结果，我们旨在详细考察中间向外策略和介观建模，并表明这些实践特别是基于认知理由对复杂问题解决任务的合理回应。然而，要提出这一主张，我们需要更新有限理性的标准概念，以考虑在这些情况下人类认知与计算是如何耦合的。我们的阐述充实了一些哲学家提出的关于计算建模与模拟“混合”性质的观点。我们所说的“耦合”既扩展了建模者处理复杂系统的能力，但也产生了各种认知和计算限制，在任何旨在对所产生的模型保持洞察力和控制的计算问题解决策略中都需要考虑这些限制。
