A Concurrent Modular Agent: Framework for Autonomous LLM Agents
This work addresses long-standing difficulties in agent architectures for AI researchers, offering a practical realization of Minsky's Society of Mind theory, though it appears incremental as it builds on existing modular and LLM-based approaches.
The paper tackles the problem of orchestrating multiple LLM-based modules in autonomous agents by introducing the Concurrent Modular Agent (CMA) framework, which enables fully asynchronous yet coherent and fault-tolerant behavior through language-mediated interactions, as demonstrated in two practical use-case studies.
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.