concept
active
concept:prior-preferences

Prior Preferences

Target distribution over states or outcomes encoded in the generative model; goal states.

Neighborhood — ranked by edge-count

Concepts (3)

concept
  • Replaces explicit reward signal in active inference; encodes agent's preferred observations independent of environment.
  • The component of expected free energy that drives utility-maximizing actions based on prior preferences over outcomes.
  • Preference Learning
    associated_with
    The ability of active inference agents to learn their own prior preferences over outcomes by accumulating Dirichlet parameters from experience.

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

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

  • Prior Intentionconcept0.830
    Cognitive bifurcation event where second-order contextual constraints reorganize semantic space, establishing weighted alternatives for action.
  • Prior Beliefsconcept0.829
    Beliefs about states before data; used to transcribe task instructions into agent's generative model
  • Self-Priorframework0.793
    The key novel contribution: an internal model that learns the density of familiar multisensory experiences and drives mark-removal behavior through mismatch with the free energy principle
  • Key element for alignment faking: model's pre-existing preferences contradict the new training objective
  • The problematic possibility of digital minds with superhumanly strong preferences requiring interpersonal utility comparison frameworks
  • Behavioral and stated consistency that implies the model is pursuing some objective, without claiming genuine internal states
  • Designing digital minds to have preferences that are trivially easy to satisfy, yielding high welfare at minimal resource cost
  • Prior expectations encoded in top-down cortical signals; balance with bottom-up input modulated by precision.