Metacognition in software agents using classifier systems
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
This paper describes a case study of the design and implementation of modeling meta cognition in software agents like CMattie by using a classifier system.
Abstract
Software agents “living ” and acting in a real world software environment, such as an operating system, a network, or a database system, can carry out many tasks for humans. Metacognition is very important for humans. It guides people to select, evaluate, revise, and abandon cognitive tasks, goals, and strategies. Thus, metacognition plays an important role in human-like software agents. Metacognition includes metacognitive knowledge, metacognitive monitoring, and metacognitive regulation. Conscious Mattie (CMattie), “living ” in a Unix machine, automatically reads and understands email concerning seminars (in natural language), and composes and distributes weekly seminar schedule announcements. CMattie implements Baar’s global workspace theory of consciousness and some other cognitive theories concerning metacognition, episodic memory, emotions, and learning. Thus, the CMattie project has its cognitive science side (cognitive modeling) as well as its computer science side (intelligent software). This paper describes a case study of the design and implementation of modeling metacognition in software agents like CMattie by using a classifier system.
