van Rooij Iris, Kwisthout Johan, Blokpoel Mark, Szymanik Jakub, Wareham Todd, Toni Ivan
Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Nijmegen, Netherlands.
Front Hum Neurosci. 2011 Jun 30;5:52. doi: 10.3389/fnhum.2011.00052. eCollection 2011.
Human intentional communication is marked by its flexibility and context sensitivity. Hypothesized brain mechanisms can provide convincing and complete explanations of the human capacity for intentional communication only insofar as they can match the computational power required for displaying that capacity. It is thus of importance for cognitive neuroscience to know how computationally complex intentional communication actually is. Though the subject of considerable debate, the computational complexity of communication remains so far unknown. In this paper we defend the position that the computational complexity of communication is not a constant, as some views of communication seem to hold, but rather a function of situational factors. We present a methodology for studying and characterizing the computational complexity of communication under different situational constraints. We illustrate our methodology for a model of the problems solved by receivers and senders during a communicative exchange. This approach opens the way to a principled identification of putative model parameters that control cognitive processes supporting intentional communication.
人类的有意交流具有灵活性和情境敏感性。假设的大脑机制只有在能够匹配展现该能力所需的计算能力时，才能对人类有意交流的能力提供令人信服且完整的解释。因此，认知神经科学了解有意交流实际的计算复杂性至关重要。尽管这一话题存在大量争论，但交流的计算复杂性至今仍不为人知。在本文中，我们捍卫这样一种观点：交流的计算复杂性并非如某些交流观点所认为的那样是一个常量，而是情境因素的函数。我们提出一种方法，用于研究和刻画不同情境约束下交流的计算复杂性。我们通过一个模型来说明我们的方法，该模型涉及在交流互动中接收者和发送者所解决的问题。这种方法为原则性地识别控制支持有意交流的认知过程的假定模型参数开辟了道路。
