在虚拟实验室中使用简单动画比较不同的认知范式及其对认知概念的启示
A Comparison of Different Cognitive Paradigms Using Simple Animats in a Virtual Laboratory, with Implications to the Notion of Cognition
摘要：
在这篇论文中，我提出了一个虚拟实验室，实现了五种不同的模型来控制动物：基于规则的系统，基于行为的系统，基于概念的系统，神经网络，和Braitenberg架构。通过不同的实验，我比较了模型的性能，并得出结论，没有“最好”的模型，因为不同的模型更好地为不同的事情在不同的上下文中。我选择的模型虽然很简单，但代表了研究认知的不同方法。使用的结果作为一个经验主义的哲学援助，我注意到，没有“最好的”方法来研究认知，因为不同的方法都有优点和缺点，因为他们从不同的背景下研究认知的不同方面。这对当前关于认知的“适当”方法的争论有影响：所有方法都有点适当，但没有一种方法是“足够适当”的。我对从所有用于研究它的方法中抽象出来的认知概念进行了评论，并对不同类型的认知提出了一个简单的分类。
英文摘要：
In this thesis I present a virtual laboratory which implements five different models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no "best" model, since different models are better for different things in different contexts. The models I chose, although quite simple, represent different approaches for studying cognition. Using the results as an empirical philosophical aid, I note that there is no "best" approach for studying cognition, since different approaches have all advantages and disadvantages, because they study different aspects of cognition from different contexts. This has implications for current debates on "proper" approaches for cognition: all approaches are a bit proper, but none will be "proper enough". I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
