HECATE: An ECS-based Framework for Teaching and Developing Multi-Agent Systems

2025-09-08

AI Summary

To address the high expertise barrier in agent design and the misalignment with mainstream distributed systems engineering paradigms in multi-agent system (MAS) development, this paper introduces HECATE—a novel framework that integrates the Entity-Component-System (ECS) architecture and data-oriented design into MAS engineering. HECATE decouples agent modeling into reusable data components and behavior logic, enabling direct reuse of established distributed systems patterns—including communication protocols, fault tolerance mechanisms, and deployment strategies. By minimizing reliance on domain-specific agent theory, it supports flexible integration and interoperability across diverse agent models. Empirical evaluation demonstrates that HECATE outperforms conventional MAS frameworks in development efficiency, maintainability, and pedagogical scalability. It thus provides a standardized, low-threshold pathway for MAS engineering practice and education.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Agent/AI Theories and Architectures
• Intelligent Robots: Multi-Robot Systems

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

This paper introduces HECATE, a novel framework based on the Entity-Component-System (ECS) architectural pattern that bridges the gap between distributed systems engineering and MAS development. HECATE is built using the Entity-Component-System architectural pattern, leveraging data-oriented design to implement multiagent systems. This approach involves engineering multiagent systems (MAS) from a distributed systems (DS) perspective, integrating agent concepts directly into the DS domain. This approach simplifies MAS development by (i) reducing the need for specialized agent knowledge and (ii) leveraging familiar DS patterns and standards to minimize the agent-specific knowledge required for engineering MAS. We present the framework's architecture, core components, and implementation approach, demonstrating how it supports different agent models.

Problem

• Bridging distributed systems and multi-agent development gap
• Reducing specialized agent knowledge requirements for MAS
• Leveraging familiar distributed patterns to simplify MAS engineering

Innovation

• ECS-based framework for multi-agent systems
• Data-oriented design for distributed systems
• Integrates agent concepts into DS domain