Cognitive Architectures for Language Agents

Summary

Draws on cognitive science and symbolic AI to propose CoALA, a framework that describes a language agent through modular memory components, a structured action space for acting on internal memory and the external environment, and a generalized decision-making process — and uses it to organize existing agents.

CommentaryA shared map for agent memory, useful precisely because it separates kinds of memory that are too often blurred together.