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A Concurrent Modular Agent: Framework for Autonomous LLM Agents

Published: August 26, 2025 | arXiv ID: 2508.19042v1

By: Norihiro Maruyama , Takahide Yoshida , Hiroki Sato and more

Potential Business Impact:

Lets AI work together to think and learn.

Business Areas:
Machine Learning Artificial Intelligence, Data and Analytics, Software

We introduce the Concurrent Modular Agent (CMA), a framework that orchestrates multiple Large-Language-Model (LLM)-based modules that operate fully asynchronously yet maintain a coherent and fault-tolerant behavioral loop. This framework addresses long-standing difficulties in agent architectures by letting intention emerge from language-mediated interactions among autonomous processes. This approach enables flexible, adaptive, and context-dependent behavior through the combination of concurrently executed modules that offload reasoning to an LLM, inter-module communication, and a single shared global state.We consider this approach to be a practical realization of Minsky's Society of Mind theory. We demonstrate the viability of our system through two practical use-case studies. The emergent properties observed in our system suggest that complex cognitive phenomena like self-awareness may indeed arise from the organized interaction of simpler processes, supporting Minsky-Society of Mind concept and opening new avenues for artificial intelligence research. The source code for our work is available at: https://github.com/AlternativeMachine/concurrent-modular-agent.

Country of Origin
🇯🇵 Japan

Repos / Data Links

Page Count
9 pages

Category
Computer Science:
Artificial Intelligence