Value learning

Value learning is a research area within artificial intelligence (AI) and AI alignment that focuses on building systems capable of inferring, acquiring, or learning human values, goals, and preferences from data, behavior, and feedback. The aim is to ensure that advanced AI systems act in ways that are beneficial and aligned with human well-being, even in the absence of explicitly programmed instructions.^[1]^[2]

^ Russell, Stuart (2019). Human Compatible: Artificial Intelligence and the Problem of Control. Viking.
^ Xu, Jisheng; Lin, Ding; Fong, Pangkit; Fang, Chongrong; Duan, Xiaoming; He, Jianping (June 2025). "Reward Models in Deep Reinforcement Learning: A Survey". arXiv:2506.09876 [cs.RO].

[1] Russell, Stuart (2019). Human Compatible: Artificial Intelligence and the Problem of Control. Viking.

[2] Xu, Jisheng; Lin, Ding; Fong, Pangkit; Fang, Chongrong; Duan, Xiaoming; He, Jianping (June 2025). "Reward Models in Deep Reinforcement Learning: A Survey". arXiv:2506.09876 [cs.RO].

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