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arXiv Open Access 2024

Metacognitive AI: Framework and the Case for a Neurosymbolic Approach

Hua Wei Paulo Shakarian Christian Lebiere Bruce Draper Nikhil Krishnaswamy +1 lainnya
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Abstrak

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.

Topik & Kata Kunci

cs.AI

Penulis (6)

H

Hua Wei

P

Paulo Shakarian

C

Christian Lebiere

B

Bruce Draper

N

Nikhil Krishnaswamy

S

Sergei Nirenburg

Format Sitasi

APA MLA BibTeX
Wei, H., Shakarian, P., Lebiere, C., Draper, B., Krishnaswamy, N., Nirenburg, S. (2024). Metacognitive AI: Framework and the Case for a Neurosymbolic Approach. https://arxiv.org/abs/2406.12147

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Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Sumber Database
arXiv
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Open Access ✓