Bryson Joanna J, Ando Yasushi, Lehmann Hagen
Artificial Models of Natural Intelligence, Department of Computer Science, University of Bath, Bath BA2 7AY, UK.
Philos Trans R Soc Lond B Biol Sci. 2007 Sep 29;362(1485):1685-98. doi: 10.1098/rstb.2007.2061.
A scientific methodology in general should provide two things: first, a means of explanation and, second, a mechanism for improving that explanation. Agent-based modelling (ABM) is a method that facilitates exploring the collective effects of individual action selection. The explanatory force of the model is the extent to which an observed meta-level phenomenon can be accounted for by the behaviour of its micro-level actors. This article demonstrates that this methodology can be applied to the biological sciences; agent-based models, like any other scientific hypotheses, can be tested, critiqued, generalized or specified. We review the state of the art for ABM as a methodology for biology and then present a case study based on the most widely published agent-based model in the biological sciences: Hemelrijk's DomWorld, a model of primate social behaviour. Our analysis shows some significant discrepancies between this model and the behaviour of the macaques, the genus used for our analysis. We also demonstrate that the model is not fragile: its other results are still valid and can be extended to compensate for these problems. This robustness is a standard advantage of experiment-based artificial intelligence modelling techniques over analytic modelling.
一般来说，一种科学方法应具备两点：其一，一种解释方式；其二，一种改进该解释的机制。基于主体的建模（ABM）是一种有助于探究个体行动选择的集体效应的方法。该模型的解释力在于其微观层面的参与者的行为能够解释观察到的宏观层面现象的程度。本文表明这种方法可应用于生物科学；基于主体的模型与任何其他科学假设一样，可以进行检验、批判、推广或细化。我们回顾了ABM作为一种生物学方法的现状，然后呈现了一个基于生物科学领域发表最为广泛的基于主体的模型的案例研究：赫梅里克的DomWorld，一个灵长类动物社会行为模型。我们的分析表明该模型与我们分析所使用猕猴属动物的行为之间存在一些显著差异。我们还证明该模型并非脆弱不堪：它的其他结果仍然有效，并且可以进行扩展以弥补这些问题。这种稳健性是基于实验的人工智能建模技术相对于分析建模的一个标准优势。
