Metacognition in Content-Centric Computational Cognitive C4 Modeling

Sergei Nirenburg; Marjorie McShane; Sanjay Oruganti

Metacognition in Content-Centric Computational Cognitive C4 Modeling

Artificial Intelligence 2025-03-25 v1

Authors: Sergei Nirenburg , Marjorie McShane , Sanjay Oruganti

Abstract

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.

Keywords

autonomous agents artificial intelligence multi-agent systems

Cite

@article{arxiv.2503.17822,
  title  = {Metacognition in Content-Centric Computational Cognitive C4 Modeling},
  author = {Sergei Nirenburg and Marjorie McShane and Sanjay Oruganti},
  journal= {arXiv preprint arXiv:2503.17822},
  year   = {2025}
}

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METACOG-25: 2nd Workshop on Metacognitive Prediction of AI Behavior

Metacognition in Content-Centric Computational Cognitive C4 Modeling

Abstract

Keywords

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