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    Chaos models provide limited but important predictive ins... — Carmelics
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    Perspectives
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    Home/Skepticism
    HistoryEditSee Inverse

    Chaos models provide limited but important predictive insight, not a complete failure of prediction.

    Causation
    ?Rate how convincing each reason is below to see the overall strength.
    1 reason for
    2 reasons against

    Reasons For

    1 perspective
    Reason for
    ?
    • 1.Detailed predictions of individual trajectories fail rapidly for chaotic models when there is any error in the specification of the initial state.
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    • 2.Instead of individual trajectory prediction, chaos models predict global behaviors and account for limited predictability.
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    • 3.Many global behaviors of chaotic models can be precisely predicted, such as control parameter values at which bifurcations occur, the onset of chaos, and the return of n-periodic orbits.
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    Reasons Against

    2 perspectives
    Reason against 1 of 2
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    • 1.Predictions of global invariants like Lyapunov exponents and attractors depend on ensemble assumptions that may not hold for any single realized system.
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    • 2.Pierre Duhem argued that physical theories require auxiliary hypotheses whose errors compound, making the isolation of 'global' from 'local' prediction philosophically untenable.
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    • 3.If the epistemic value of prediction requires applicability to particular outcomes, statistical descriptions of attractors fail the standard set by Hempel's covering-law model of scientific explanation.
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    Reason against 2 of 2
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    • 1.Nancy Cartwright's critique of idealization holds that models abstracting away trajectory specifics trade predictive content for mathematical tractability, not genuine insight.
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    • 2.A prediction that specifies only the topology of possible behaviors without determining which behavior obtains provides no discriminating power between competing hypotheses about the actual world.
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    Related

    A prediction that specifies only the topology of possible behaviors without dete...Detailed predictions of individual trajectories fail rapidly for chaotic models ...If the epistemic value of prediction requires applicability to particular outcom...Instead of individual trajectory prediction, chaos models predict global behavio...
    +4 moreShow less
    Many global behaviors of chaotic models can be precisely predicted, such as cont...Nancy Cartwright's critique of idealization holds that models abstracting away t...Pierre Duhem argued that physical theories require auxiliary hypotheses whose er...Predictions of global invariants like Lyapunov exponents and attractors depend o...

    Similar

    False models can be used as means to arrive at true theories78%Idealized assumptions of a model are explanatorily irrelevant.77%Toy models are illustrative of techniques but are misleadingly simple ...77%The idealized assumptions of a model do not make a difference to the p...76%

    Source

    AI-extracted1/3 agreementValid
    SEP: chaos
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    Regarding (1), detailed predictions regarding individual trajectories fail rather rapidly for chaotic models when there is any error in specification of the initial state. So, says Kellert, instead we predict global behaviors of models and have an account of limited predictability in chaotic models. But many of these behaviors can be precisely predicted (e.g., control parameter values[9] at which various bifurcations occur, the onset of chaos, the return of n-periodic orbits). (1) amounts to i
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    Details

    Type
    claim
    Perspectives
    3 (1 for, 2 against)
    Edits
    1 edit