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cs.AI2026
Learning the Preferences of a Learning Agent
Karim Abdel Sadek, Mark Bedaywi, Rhys Gould +1
For AI systems to be useful to humans, they must understand and act in accordance with our values and preferences. Since specifying preferences is a hard task, inverse reinforcemen…
cs.AI2025
Observation Interference in Partially Observable Assistance Games
Scott Emmons, Caspar Oesterheld, Vincent Conitzer +1
We study partially observable assistance games (POAGs), a model of the human-AI value alignment problem which allows the human and the AI assistant to have partial observations. Mo…