Revealed Preferences

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Preference Learningconcept0.771
  The ability of active inference agents to learn their own prior preferences over outcomes by accumulating Dirichlet parameters from experience.
• Inexpensive Preferencesconcept0.770
  Designing digital minds to have preferences that are trivially easy to satisfy, yielding high welfare at minimal resource cost
• Preference Strengthconcept0.767
  The problematic possibility of digital minds with superhumanly strong preferences requiring interpersonal utility comparison frameworks
• Prior Preferencesconcept0.766
  Target distribution over states or outcomes encoded in the generative model; goal states.
• Selectivitymethod0.763
  Adapted control task metric measuring difference between odds-ratio on original task and arbitrary-label control task
• Preference Conflictconcept0.762
  Key element for alignment faking: model's pre-existing preferences contradict the new training objective
• Preferred Distributionconcept0.754
  In active inference, the distribution over goal states; here replaced by the learned self-prior rather than a hand-specified prior
• Preference Modelframework0.742
  A model trained on comparison data to assign scores to responses, used as reward signal in RLHF/RLAIF.