Agent Communication Languages

Collaborative Discussion Post Summary

Building on the insightful responses from my peers, it is obvious that understanding multi-agent systems starts with understanding the distinction between agents and method invocation in object-oriented programming. As highlighted in my initial post, autonomy is one of the most important aspects of agents, this is how they retain control over action execution, as opposed to the mandatory execution of methods in OOP (Wooldridge, 2009). Both Thiago and Deane emphasise this, rightfully noting that agent communication languages (ACLs) are designed not for rule enforcing, but to facilitate communication and facilitate decision-making.

KQML, as a lightweight and flexible language, allows for basic information exchange, while FIPA ACL offers richer semantics and structure, making it better suited for complex domains such as smart cities and autonomous robotics. Thiago points to the practical challenges of semantic mismatches, even in the case of FIPA ACL (Payne and Tamma, 2014), while Deane underlines the potential of hybrid solutions that unites the efficiency of method invocation with the benefits of ACLs. Both perspectives further strengthen my initial argument that existing limitations can be solved through ongoing improvements on protocols and adaptability.

Additionally, as Thiago mentions, the emergence of protocols like the Model Context Protocol (MCP) that could function alongside ACLs offer an intriguing solution. MCP offers a middleware-style approach that lets agents keep track of conversations and tasks while connecting to external tools and data (Ray, 2025). If ACLs remain the mediator for agent-to-agent negotiation, and MCP acts as the foundation for an individual agent to manage both context and external resources, this could provide high-level communication and the practical tools needed for complex tasks.

In conclusion, all these discussions highlight that, while ACLs come with limitations, they lay the groundwork for agent autonomy and cooperation. The next step is to develop their adaptability and efficiency, possibly through hybrid systems and protocols such as MCP, to keep up with increasingly complex environments.