Understand
Agentic AI seeks to endow systems with sustained autonomy, reasoning, and interaction capabilities.
- To realize this vision, its assumptions about agency must be complemented by explicit models of cognition, cooperation, and governance.
- This paper argues that the conceptual tools developed within the Autonomous Agents and Multi-Agent Systems (AAMAS) community, such as BDI architectures, communication protocols, mechanism design, and institutional modelling, provide precisely such a foundation.
- By aligning adaptive, data-driven approaches with structured models of reasoning and coordination, we outline a path toward agentic systems that are not only capable and flexible, but also transparent, cooperative, and accountable.