Cognitive Architectures for Language Agents
Source
- Person key:
ysymyth - Source kind:
paper - Canonical URL: https://arxiv.org/abs/2309.02427
- License:
NOASSERTION - Public handling:
public-metadata-summary-hash-link-only - Semantic hash:
21be0814779f8ec4af572a3417e9fda14a44ea5947a2a4b42837a0c3cf37de98 - First seen: 2026-05-16
- Last changed: 2026-05-16
- Identity guard: Do not confuse with yao-shunyu-alfred, the physics-to-AI researcher at alfredyao.github.io.
Classification
- Category: Language agents / agent architectures
- Topic hub: shunyu-yao-public-corpora
- Project taxonomy: shunyu-yao-project-taxonomy
- Paper map: shunyu-yao-paper-map
Summary
Recent efforts have augmented large language models (LLMs) with external resources (e.g., the Internet) or internal control flows (e.g., prompt chaining) for tasks requiring grounding or reasoning, leading to a new class of language agents. While these agents have achieved substantial empirical success, we lack a systematic framework to organize existing agents and plan future developments. In this paper, we draw on the rich history of cognitive science and symbolic artificial intelligence to propose Cognitive Arch…
What This Teaches
How language models become agents through reasoning, acting, memory, tools, and interface design.
Related
Public Handling Notes
- EXTRACTED: Metadata and links are from public sources.
- INFERRED: Unclear-license full text, PDFs, and source code should not be mirrored into public wiki pages.
- AMBIGUOUS: Items discovered by keyword search are still separated by source identity and category heuristics.