"any goal or purpose can be well thought of as maximization of the expected value of the cumulative sum of a received scalar signal (reward)"

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• acting to optimize value and perception are two aspects of exactly the same principle; namely the minimisation of a quantity [free energy] that bounds the probability of sensory input, given a particular agent or phenotype.quote0.792
  Concise statement of the free-energy principle's unification of action and perception.
• Under active inference, the ultimate ‘goal’ is to maintain a coherent phenotype and persist over time, not to maximize reward.claim0.777
  §3, preference learning discussion.
• Mean Cumulative Objective Rewardmethod0.777
  Primary performance metric: total food visits across agent lifetime
• Acting to optimize value and perception are two aspects of exactly the same principle: minimization of free energy.claim0.770
  Foundational claim unifying action and perception within single optimization framework.
• Acting to maximize value is the same as acting to minimize surprise; value is simply the probability of sensory input expected by an agent.claim0.770
  Reinterprets classical reward/value concepts through free energy lens.
• Curiosity, insight, decision-making, and diverse phenomena can all be accommodated by a single imperative: minimization of expected free energy (resolution of uncertainty).claim0.768
  Central thesis of the paper unifying cognitive phenomena under one objective function
• Optimizing toward the simulation objective does not incentivize instrumentally convergent behaviors the way that reward functions which evaluate trajectories do.claim0.766
  Deontological nature of predictive loss.
• A model whose objective is prediction can simulate agents who optimize toward any objectives, with any degree of optimality (bounded above but not below by the model's power).claim0.765
  Prediction orthogonality thesis.