METACOG-26: Symposium on Artificial Metacognition

We are proposing METACOG-2026 to be part of the AAAI Fall Symposium. This page is designed to provide some basic information.

1. Symposium Description

Artificial Metacognition is the ability for an AI system to reason about itself.  The idea is based on a concept in cognitive psychology [1, 2]. In the early 2000s, AAAI held several symposia on this topic [3, 4]. Recently, due to the advent of the LLM, neurosymbolic AI, and the need for more robust AI systems, this topic has re-emerged in a series of small venues [5, 6] and most recently an “emerging trends” talk at AAAI-2026 [7].  The study of metacognition goes beyond related topics such as out-of-distribution detection and uncertainty quantification by not only detecting when a model could potentially be in an error mode, but determining aspects about security, computational efficiency, power usage, explainability, and corrective action in a unified, often cognitively inspired, framework.  Recent events have brought together researchers from computer science, cognitive psychology, electrical engineering, mechanical engineering, systems engineering, and mathematics.  The proposed Symposium on Artificial Metacognition will continue this exploration by inviting papers featuring a variety of methodologies that have been explored in the recent literature, including stress testing of robotic systems, model introspection, model certification, performance prediction, critique models for LLMs, metacognitive rule learning, and metacognitive extensions to cognitive architectures such as ACT-R and the Common Model of Cognition.

2. Objectives

The objectives of the symposium are as follows:

  • Survey and synthesize current approaches to metacognition in AI systems, including monitoring, control, and metareasoning.
  • Understand the requirements for and trade-offs among various metacognitive approaches.
  • Identify novel methods for metacognition that improve AI performance in operational, out-of-distribution, and cross-domain settings.
  • Identify application areas suitable for the deployment of metacognitive methods, including autonomy, cyber, vision, robotics, and decision support.
  • Foster cross-disciplinary collaboration between AI, cognitive psychology, cognitive modeling, control theory, and systems engineering.
  • Examine the relationship between AI metacognition and human operators, including trust, calibration, and human-AI teaming.

3 Topics of Interest

Specific topics to be covered include, but are not limited to:

  • AI Agents with Metacognition (LLM-based agents, autonomous agents, and embodied agents that self-monitor and self-regulate).
  • Cognitive model architectures with metacognitive extensions (e.g., ACT-R, Soar, the Common Model of Cognition).
  • Metacognitive rule learning (data-driven and neuro-symbolic learning of error-detection and constraint rules).
  • Critique models (training, evaluation, and deployment of models that produce natural-language feedback on the outputs of other AI systems).
  • Explainable performance prediction of black-box AI systems.
  • Stress testing of reinforcement learning and perception systems.
  • Metacognitive monitoring vs. metacognitive control, including metareasoning and resource regulation.
  • Neuro-symbolic AI architectures for metacognition.
  • Self-adaptive, self-healing, and self-repairing AI systems for new domains.
  • Out-of-distribution detection, abductive inference, and consistency-based verification as metacognitive cues.
  • Trust calibration, human-in-the-loop metacognition, and human-AI teaming.
  • Datasets, benchmarks, and evaluation methodology for metacognitive AI.
  • Applications of metacognitive AI to autonomy, robotics, cyber operations, and decision support.

4. Symposium Format

METACOG-26 will be a 2.5-day symposium following the standard AAAI Fall Symposium structure. Programming will combine traditional paper sessions with extended discussion, a poster session, two invited keynotes, and a closing panel. This structure is consistent with the symposium series’ emphasis on intimate forums and substantive discussion. We anticipate accepting up to 14 full papers (oral) and up to 12 posters. Submission will be peer-reviewed by the organizing committee and a small program committee drawn from the prior workshops. Accepted papers will be published in the AAAI Technical Report series.

5. Organizing Committee

Paulo Shakarian (Syracuse)

Nathaniel D. Bastian (West Point)

Francesco Restuccia (Northeastern)

Christian Lebiere (Carnegie Mellon)

Arslan Basharat (KitWare)