Centre for Vision, Speech and Signal Processing, Faculty of Engineering & Physical Sciences, University of Surrey, Guildford, UK.
Adv Exp Med Biol. 2010;657:95-134. doi: 10.1007/978-0-387-79100-5_6.
As well as having the ability to formulate models of the world capable of experimental falsification, it is evident that human cognitive capability embraces some degree of representational plasticity, having the scope (at least in infancy) to modify the primitives in terms of which the world is delineated. We hence employ the term 'cognitive bootstrapping' to refer to the autonomous updating of an embodied agent's perceptual framework in response to the perceived requirements of the environment in such a way as to retain the ability to refine the environment model in a consistent fashion across perceptual changes.We will thus argue that the concept of cognitive bootstrapping is epistemically ill-founded unless there exists an a priori percept/motor interrelation capable of maintaining an empirical distinction between the various possibilities of perceptual categorization and the inherent uncertainties of environment modeling.As an instantiation of this idea, we shall specify a very general, logically-inductive model of perception-action learning capable of compact re-parameterization of the percept space. In consequence of the a priori percept/action coupling, the novel perceptual state transitions so generated always exist in bijective correlation with a set of novel action states, giving rise to the required empirical validation criterion for perceptual inferences. Environmental description is correspondingly accomplished in terms of progressively higher-level affordance conjectures which are likewise validated by exploratory action.Application of this mechanism within simulated perception-action environments indicates that, as well as significantly reducing the size and specificity of the a priori perceptual parameter-space, the method can significantly reduce the number of iterations required for accurate convergence of the world-model. It does so by virtue of the active learning characteristics implicit in the notion of cognitive bootstrapping.
除了具有能够制定可进行实验反驳的世界模型的能力外，人类认知能力显然还具有一定程度的代表性可塑性，能够（至少在婴儿期）根据世界的描述方式来修改原始信息。因此，我们使用“认知引导”这个术语来指代自主更新体现代理的感知框架，以响应环境感知到的要求，从而保持在感知变化的情况下以一致的方式细化环境模型的能力。因此，我们将论证，除非存在一种先验的感知/运动相互关系，能够在感知分类的各种可能性与环境建模的固有不确定性之间保持经验上的区别，否则认知引导的概念在认识论上是没有根据的。作为这个想法的实例，我们将指定一个非常通用的、逻辑归纳的感知-行动学习模型，该模型能够对感知空间进行紧凑的重新参数化。由于先验的感知/动作耦合，所生成的新颖感知状态转换总是与一组新颖的动作状态存在一一对应关系，从而为感知推断提供了所需的经验验证标准。环境描述相应地是根据逐步更高层次的可供性假设来完成的，这些假设同样通过探索性动作来验证。在模拟感知-动作环境中应用这种机制表明，该方法不仅可以显著减小先验感知参数空间的大小和特异性，还可以通过认知引导的主动学习特性显著减少准确收敛世界模型所需的迭代次数。
