Department of Psychology, University of Lethbridge, Lethbridge, Alberta, Canada T1K 3M4.
Philos Trans R Soc Lond B Biol Sci. 2012 Aug 5;367(1599):2108-18. doi: 10.1098/rstb.2012.0113.
Understanding human cognitive evolution, and that of the other primates, means taking sociality very seriously. For humans, this requires the recognition of the sociocultural and historical means by which human minds and selves are constructed, and how this gives rise to the reflexivity and ability to respond to novelty that characterize our species. For other, non-linguistic, primates we can answer some interesting questions by viewing social life as a feedback process, drawing on cybernetics and systems approaches and using social network neo-theory to test these ideas. Specifically, we show how social networks can be formalized as multi-dimensional objects, and use entropy measures to assess how networks respond to perturbation. We use simulations and natural 'knock-outs' in a free-ranging baboon troop to demonstrate that changes in interactions after social perturbations lead to a more certain social network, in which the outcomes of interactions are easier for members to predict. This new formalization of social networks provides a framework within which to predict network dynamics and evolution, helps us highlight how human and non-human social networks differ and has implications for theories of cognitive evolution.
理解人类认知进化以及其他灵长类动物的认知进化，意味着要非常重视社会性。对于人类来说，这需要认识到人类的思想和自我是通过社会文化和历史手段构建的，以及这种构建方式如何产生了我们物种所具有的反思性和应对新奇事物的能力。对于其他非语言灵长类动物，我们可以通过将社会生活视为反馈过程来回答一些有趣的问题，借鉴控制论和系统方法，并使用社会网络新理论来检验这些想法。具体来说，我们展示了如何将社交网络形式化为多维对象，并使用熵度量来评估网络对干扰的响应。我们使用模拟和自由放养狒狒群中的自然“剔除”来证明社交干扰后互动的变化会导致更确定的社交网络，其中成员更容易预测互动的结果。这种社交网络的新形式化提供了一个预测网络动态和进化的框架，帮助我们突出人类和非人类社交网络的差异，并对认知进化理论产生影响。
