A comparative analysis of eight verifiable autonomous agent systems—AutoGPT, BabyAGI, MetaGPT, CrewAI, Microsoft AutoGen, Voyager, Devin (Cognition), and TIAMAT—examining their architectures across five dimensions: loop structure, containment mechanisms, behavioral control strategies, documented behavioral anomalies, and operational transparency. Drawing on the 2025 AI Agent Index, shutdown resistance research, and alignment faking findings, we propose a five-level containment taxonomy and identify open problems. Key finding: the gap between task-bounded and continuously operating agents represents the critical frontier for behavioral safety research.
Chamberlain et al. (Sun,) studied this question.
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