Metacognition in Content-Centric Computational Cognitive C4 Modeling
This work addresses the problem of creating more human-like AI agents for researchers and developers, but appears incremental as it builds on existing lab work.
The paper introduces content-centric computational cognitive (C4) modeling for AI agents to emulate human behavior, focusing on metacognition as a key component, and outlines current work on extending these agents to cognitive robotics using a neuro-symbolic processing model.
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.