Testing BDI-based Multi-Agent Systems using Discrete Event Simulation

2026-02-14

AI Summary

This work addresses the challenge of testing BDI multi-agent systems, which are inherently difficult to evaluate due to their openness and unpredictability. Existing simulation approaches often require modifications to the original agent code, introducing a reality gap that compromises fidelity. To overcome this limitation, the paper proposes a high-fidelity simulation method that operates without altering native BDI code. It introduces the first native mapping of BDI agent control flow into a discrete-event simulation (DES) framework and designs a multi-granularity mapping mechanism to balance simulation fidelity and computational efficiency. An open-source prototype system is implemented using JaKtA and Alchemist, and experimental results demonstrate how different mapping granularities affect simulation outcomes, offering a practical and efficient testing solution for BDI multi-agent systems.

Technology Category

• Multiagent Systems: Agent-Based Simulation and Emergent Behavior
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Web Mining and Content Analysis: Web data generation and simulation

Abstract

Multi-agent systems are designed to deal with open, distributed systems with unpredictable dynamics, which makes them inherently hard to test. The value of using simulation for this purpose is recognized in the literature, although achieving sufficient fidelity (i.e., the degree of similarity between the simulation and the real-world system) remains a challenging task. This is exacerbated when dealing with cognitive agent models, such as the Belief Desire Intention (BDI) model, where the agent codebase is not suitable to run unchanged in simulation environments, thus increasing the reality gap between the deployed and simulated systems. We argue that BDI developers should be able to test in simulation the same specification that will be later deployed, with no surrogate representations. Thus, in this paper, we discuss how the control flow of BDI agents can be mapped onto a Discrete Event Simulation (DES), showing that such integration is possible at different degrees of granularity. We substantiate our claims by producing an open-source prototype integration between two pre-existing tools (JaKtA and Alchemist), showing that it is possible to produce a simulation-based testing environment for distributed BDI} agents, and that different granularities in mapping BDI agents over DESs may lead to different degrees of fidelity.

Problem

• BDI agents
• multi-agent systems
• discrete event simulation
• simulation fidelity
• testing

Innovation

• BDI agents
• Discrete Event Simulation
• simulation fidelity
• multi-agent systems
• control flow mapping