Autonomous agents is one of the most popular topics in the foundation model ecosystem. The early iteration of projects such as AutoGPT or BabyAGI sparked developers' imagination about the possibilities of autonomously solving tasks using large language models(LLMs). Many researchers believe that autonomous agents are one of the next frontiers in foundation models. However, the definition of what constitutes an agent is very loose today. Recently, researchers from AIWaves Zhejiang University and ETH Zürich published a paper detailing AGENTS, a framework for the creation of LLM-powered agents.

The core idea behind AGENTS is to expand this concept beyond the confines of research circles and onto a more mainstream audience. AGENTS tries to incorporate important building blocks such as planning, memory, tool usage, multi-agent communication, and symbolic control under a single programming model. The paper comes accompanied by an open-source release, which is quite easy to use.

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