The paper proposes a developmental framework for autonomous artificial agents that emphasizes learning social norms and alignment through direct interaction with dynamic environments. It argues that intrinsic motivations such as curiosity and competence can guide exploration, but also complicate alignment with human goals. By drawing parallels to child development, the authors suggest that regulatory sandboxes serve as pedagogical spaces where agents gradually acquire moral agency and adapt their behaviors through experience and cooperation.
By Marica Notte, Ludovica Marinucci, Vieri Giuliano Santucci
arXiv:2606. 13196v2 Announce Type: replace Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
By Yong Zeng
arXiv:2606. 13196v1 Announce Type: new Abstract: Recent AI systems can generate texts, software architectures, hypotheses, designs, and scientific workflows that appear creative.
By Yong Zeng
The paper reviews how large language models have evolved into agents that can influence external environments through tool use, interface operation, delegation, state retention, virtual world inhabitation, and robotic control. It critiques the narrative of a single march toward autonomy, distinguishing model competence from system integration, persistence, and safe authority. The authors find that action-interface expansion is well documented, while robust completion, recovery, authorization, and independent verification remain less proven, and they propose a framework of justified delegation to guide future research.
By Linsen Zhu, Mengqing Cai
arXiv:2507. 05169v4 Announce Type: replace-cross Abstract: World Model, the algorithmic simulator of the real-world environment which biological agents experience and act upon, has been an emerging topic in recent years due to the rising need to develop virtual agents with artificial (general) intelligence.
By Eric Xing, Mingkai Deng, Jinyu Hou
arXiv:2507. 05169v5 Announce Type: replace-cross Abstract: World Model, the algorithmic simulator of the real-world environment which biological agents experience and act upon, has been an emerging topic in recent years due to the rising need to develop virtual agents with artificial (general) intelligence.
By Eric Xing, Mingkai Deng, Jinyu Hou