GoalfyMax: A Protocol-Driven Multi-Agent System for Intelligent Experience Entities
Siyi Wu, Zeyu Wang, Xinyuan Song, Zhengpeng Zhou, Lifan Sun, and Tianyu Shi

TL;DR
GoalfyMax is a protocol-driven multi-agent system that enhances coordination, memory reuse, and task decomposition through standardized communication and layered memory architecture, enabling scalable and adaptable intelligent enterprise solutions.
Contribution
It introduces a novel protocol-driven framework with a standardized communication layer and layered memory system for improved multi-agent collaboration and continual learning.
Findings
Achieves superior adaptability and coordination in complex tasks
Demonstrates effective experience reuse and knowledge retention
Outperforms baseline frameworks on benchmark tasks
Abstract
Modern enterprise environments demand intelligent systems capable of handling complex, dynamic, and multi-faceted tasks with high levels of autonomy and adaptability. However, traditional single-purpose AI systems often lack sufficient coordination, memory reuse, and task decomposition capabilities, limiting their scalability in realistic settings. To address these challenges, we present \textbf{GoalfyMax}, a protocol-driven framework for end-to-end multi-agent collaboration. GoalfyMax introduces a standardized Agent-to-Agent (A2A) communication layer built on the Model Context Protocol (MCP), allowing independent agents to coordinate through asynchronous, protocol-compliant interactions. It incorporates the Experience Pack (XP) architecture, a layered memory system that preserves both task rationales and execution traces, enabling structured knowledge retention and continual learning.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsContext-Aware Activity Recognition Systems · Distributed and Parallel Computing Systems · Cognitive Computing and Networks
