The Role of Cognitive Architectures for Generative AI Agents: An Exploration based on AutoGen and CoALA

AAMAS 2026 Workshop EMAS Submission38 Authors

Keywords: Cognitive Architecture, Generative AI, Agentic AI

Abstract: Advances in generative AI have led to the emergence of several practical frameworks for developing agents based on generative models. On the one hand, these frameworks are effective enabling technologies, allowing for flexibly exploiting Large Language Models (LLMs). On the other hand, they typically do not provide any specific high-level architectural blueprint for designing agents, as those found instead in research contexts. To this purpose, in this paper we present a prototype framework called Cognitive AutoGen (CoAG), that enriches AutoGen - which is a well-known and widely adopted practical framework for developing LLM-based autonomous agents - with a cognitive layer, inspired by the CoALA (Cognitive Architectures for Language Agents) cognitive architecture proposal. Besides the framework, we describe the assessment framework that we used to compare regular AutoGen agents against the ones implemented with CoAG, along with a first case study and results.

Paper Type: Student paper

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Submission Number: 38