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question:how-do-simple-components-with-only-local-rewardsHow Do Simple Components With Only Local Rewards
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- Authors argue the prevalence of token-in-context features reflects genuine model computation rather than dictionary learning artifact
- Interpretation of the experimental finding: overlapping local symmetries are the hidden structural feature that creates perceived wholeness
- Core thesis of the paper framed against the historical challenge of hand-crafting CA rules
- Generalization from the door examples.
- Central research question defining the scope of physical learning; asks about achievable learning under locality constraints
- At each step, doing the simplest thing that can be done to intensify existing centers will produce living structure.hypothesis0.684Operational hypothesis equating simplicity of step with emergence of life.
- Theoretical distinction between representing token-context pairs as individual features (local) vs combining independent features (compositional)