Metacognitive AI: Framework and the Case for a Neurosymbolic Approach

TL;DR

A framework for understanding metacognitive artificial intelligence (AI) that is introduced that discusses transparency, reasoning, adaptation, and perception and explores how neurosymbolic AI (NSAI) can be leveraged to address challenges of metacognition.

Abstract

Metacognition is the concept of reasoning about an agent's own internal processes and was originally introduced in the field of developmental psychology. In this position paper, we examine the concept of applying metacognition to artificial intelligence. We introduce a framework for understanding metacognitive artificial intelligence (AI) that we call TRAP: transparency, reasoning, adaptation, and perception. We discuss each of these aspects in-turn and explore how neurosymbolic AI (NSAI) can be leveraged to address challenges of metacognition.

Figures (1)

• Figure 1: Four aspects of metacognitive AI (TRAP) and approaches to achieve metacognition.