Titlebook: Explainable, Transparent Autonomous Agents and Multi-Agent Systems; Second International Davide Calvaresi,Amro Najjar,Kary Främling Confere

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In-Time Explainability in Multi-Agent Systems: Challenges, Opportunities, and Roadmapng exploitation of ML-based approaches generated opaque systems, which are nowadays no longer socially acceptable—calling for eXplainable AI (XAI). Such a problem is exacerbated when IS tend to approach safety-critical scenarios. This paper highlights the need for on-time explainability. In particul

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Valery M. Kaziev,Lyudmila V. Glukhova agents using two different algorithms which automatically generate different explanations for agent actions. Quantitative analysis of three user groups (n = 20, 25, 20) in which users detect the bias in agents’ decisions for each explanation type for 15 test data cases is conducted for three differ

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Explainable, Transparent Autonomous Agents and Multi-Agent SystemsSecond International

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