An Episode Tracker for Cognitive Architectures
摘要
This paper introduces the Episode Tracker Module, an encoding mechanism that tracks sensory information through space and time, building up high-level semantic representations called episodes. This module is aimed to extend the Cognitive Systems Toolkit (CST) as a reusable framework for building different cognitive models for episode detection. We created two instances of the episode tracker with two different mechanisms for identifying property categories (geographical regions). Each mechanism correctly induced a different episode detection dynamic. Overall, the Episode Tracker architecture provides a robust and flexible framework for episode detection.