# Metacognition in Content-Centric Computational Cognitive C4 Modeling

arXiv: https://arxiv.org/abs/2503.17822 · HTML: https://mlsanity.com/paper/2503.17822/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 14 references that are in the map.
- First posted on arXiv 22 Mar 2025.

## Builds on (most cited first, 2 of 2)

- [Neural-Symbolic Learning and Reasoning: A Survey and Interpretation](https://mlsanity.com/paper/1711.03902/) (2017)
- [HARMONIC: A Framework for Explanatory Cognitive Robots](https://mlsanity.com/paper/2409.18037/) (2024)

## Abstract (arXiv)

For AI agents to emulate human behavior, they must be able to perceive, meaningfully interpret, store, and use large amounts of information about the world, themselves, and other agents. Metacognition is a necessary component of all of these processes. In this paper, we briefly a) introduce content-centric computational cognitive (C4) modeling for next-generation AI agents; b) review the long history of developing C4 agents at RPI's LEIA (Language-Endowed Intelligent Agents) Lab; c) discuss our current work on extending LEIAs' cognitive capabilities to cognitive robotic applications developed using a neuro symbolic processing model; and d) sketch plans for future developments in this paradigm that aim to overcome underappreciated limitations of currently popular, LLM-driven methods in AI.