Book contents
- Frontmatter
- Contents
- Contributors
- Acknowledgments
- Part I Introduction
- Part II Taxonomy of Metacognitive Approaches
- Part III Neuro-Symbolic Models in AI
- Part IV Metacognition with LLMS
- Part V Metacognition in Learning Agents
- Part VI Assured Machine Learning in High-Stakes Domains
- Part VII Metacognition as a Solution to Handle Failure
- 13 Reasoning about Anomalous Object Interaction Using Plan Failure as a Metacognitive Trigger
- 14 Tractable Probabilistic Reasoning for Trustworthy AI
- Part VIII Applications of Metacognitive AI
13 - Reasoning about Anomalous Object Interaction Using Plan Failure as a Metacognitive Trigger
from Part VII - Metacognition as a Solution to Handle Failure
Published online by Cambridge University Press: aN Invalid Date NaN
Book contents
- Frontmatter
- Contents
- Contributors
- Acknowledgments
- Part I Introduction
- Part II Taxonomy of Metacognitive Approaches
- Part III Neuro-Symbolic Models in AI
- Part IV Metacognition with LLMS
- Part V Metacognition in Learning Agents
- Part VI Assured Machine Learning in High-Stakes Domains
- Part VII Metacognition as a Solution to Handle Failure
- 13 Reasoning about Anomalous Object Interaction Using Plan Failure as a Metacognitive Trigger
- 14 Tractable Probabilistic Reasoning for Trustworthy AI
- Part VIII Applications of Metacognitive AI
Summary
In this chapter, we use task failure as a trigger to engage in metacognitive processes. We present a procedure by which an agent may exploit failure in the zero-shot outputs of LLMs as a trigger to investigate alternative solutions to the problem using object interactions and knowledge of the object semantics. We additionally propose a method through which knowledge gained from the object interactions can be distilled back into the LLM and avenues for future research.
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- Metacognitive Artificial Intelligence , pp. 231 - 244Publisher: Cambridge University PressPrint publication year: 2025
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