Article Dans Une Revue Autonomous Agents and Multi-Agent Systems Année : 2025

A multi-level explainability framework for engineering and understanding BDI agents

Résumé

Abstract As the complexity of software systems rises, explainability - i.e. the ability of systems to provide explanations of their behaviour - becomes a crucial property. This is true for any AI-based systems, including autonomous systems that exhibit decisionmaking capabilities such as multi-agent systems. Although explainabil- ity is generally considered useful to increase the level of trust for end-users, we argue it is also an interesting property for software engineers, developers, and designers to debug and validate the system’s behaviour. In this paper, we propose a multi-level explainability framework for BDI agents to generate explanations of a running system from logs at different levels of abstraction, tailored to different users and their needs. We describe the mapping from logs to explanations, and present a prototype tool based on the JaCaMo platform which implements the framework.

Dates et versions

hal-04932263 , version 1 (06-02-2025)

Identifiants

Citer

Elena Yan, Samuele Burattini, Jomi Fred Hübner, Alessandro Ricci. A multi-level explainability framework for engineering and understanding BDI agents. Autonomous Agents and Multi-Agent Systems, 2025, 39 (1), pp.9. ⟨10.1007/s10458-025-09689-6⟩. ⟨hal-04932263⟩
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