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The Way Not TakenThe Way Not Takenoror
How to Do Things with anHow to Do Things with an Infinite RegressInfinite Regress
Two Methodological Paradigms Two Methodological Paradigms
Certainty
Problem of induction
. . .
“perfect support”
Two Methodological Paradigms Two Methodological Paradigms
Certainty
ConfirmationConfirmation
Partial support
“perfect support”
Two Methodological Paradigms Two Methodological Paradigms
Halting with the right answer
Certainty
ConfirmationConfirmation
Partial support
“perfect support”
Eureka!
Two Methodological Paradigms Two Methodological Paradigms
Entailment by evidence Halting with the right answer
Certainty
ConfirmationConfirmation LearningLearning
Partial support Convergent procedure
Eureka!
Two Methodological Paradigms Two Methodological Paradigms
Entailment by evidence Halting with the right answer
Certainty
ConfirmationConfirmation LearningLearning
Partial support Convergent procedure
Two Methodological Paradigms Two Methodological Paradigms
Entailment by evidence Halting with the right answer
Certainty
ConfirmationConfirmation LearningLearning
Partial support Convergent procedure
•Relational state
•“Internal”
•Relation “screens off” process
•Computation is extraneous
•Dynamical stability
•“External”
•Process paramount
•Computational perspective
ConfirmationConfirmation
What justifies the confirmation relation?
The Ultimate QuestionThe Ultimate Question
What justifies methods?
OptionsOptions. . .. . .. . .
FoundationalismA priori justification
CoherentismMethods justify themselves
RegressAlways respond with a new method
Alternative Approach Alternative Approach
ConfirmationConfirmation LearningLearning
What justifies the confirmation relation?
How can we learn whether we are learning?
What Justifies Science?
Learning Theory PrimerLearning Theory Primer
MM
epistemically relevant worlds
method
hypothesis
data stream1 0 1 0 ? 1 ? 1 0 ? ? ?1 0 1 0 ? 1 ? 1 0 ? ? ?
correctness
conjecture stream
H
K
PutnamWeinsteinGoldFreiwaldBarzdinBlumCaseSmithSharmaDaleyOshersonEtc.
ConvergenceConvergence
MMIn the limit: ? ? 0 ? 1 0 1 0 1 1 1 1…
finite forever
MMWith certainty: ? ? 0 ? 1 0 1 0 halt!
finite
= Guaranteed convergence to the right answer
MMKH
Verification Refutation Decision
Converge to 1Don’t
converge to 0Converge to 1
Don’t
converge to 1Converge to 0 Converge to 0
ReliabilityReliability
1-sided 2-sided
wor
lds
data
conj
ectu
res
Some Some Reliability ConceptsReliability Concepts
Decision Verification Refutation
Certain Halt with correct answer
Halt with “yes” iff true
Halt with “no” iff false
Limiting Converge to correct answer
Converge to “yes” iff true
Converge to “no” iff false
One-sidedTwo-sided
Example: UniformitariansmExample: UniformitariansmMichael Ruse, Michael Ruse, The Darwinian RevolutionThe Darwinian Revolution
Uniformitarianism (steady-state)
Catastrophism (progressive):
Com
plex
ity
Com
plex
ity
Stonesfield mammals
creation
Uniformitarianism is refutable in the limit: – Side with uniformitarianism each time the
current progressive schedule is violated.– Eventually slide back to progressionism after
the revised schedule stands up for a while.
Example: UniformitariansmExample: UniformitariansmMichael Ruse, Michael Ruse, The Darwinian RevolutionThe Darwinian Revolution
Historicism ExplainedHistoricism Explained
Articulations refutable only in a paradigm.Articulations crisply refutable with a
paradigm.No time at which a paradigm must be
rejected. Method inputs needn’t be cognized.Propositions forced by inputs relative to a
paradigm may be paradigm-relative.
UnderdeterminationUnderdetermination = = Degrees of UnsolvabilityDegrees of Unsolvability
Verifiable inthe limit
Verifiable inthe limit
Refutable in the limit
Refutable in the limit
Decidablewith certainty
Decidablewith certainty
Decidable inthe limit
Decidable inthe limit
Verifiablewith certainty
Verifiablewith certainty
Refutablewith certainty
Refutablewith certainty
Verifiable inthe limit
Verifiable inthe limit
Refutable in the limit
Refutable in the limit
Decidablewith certainty
Decidablewith certainty
Decidable inthe limit
Decidable inthe limit
Verifiablewith certainty
Verifiablewith certainty
Refutablewith certainty
Refutablewith certainty
•Catastrophism•The coin is unfair•Computability
•Uniformitarianism•The coin is fair
•Uncomputability
•It will rain tomorrow
•Phenomenal laws•Observable existence
UnderdeterminationUnderdetermination = = Degrees of UnsolvabilityDegrees of Unsolvability
UnderdeterminationUnderdetermination = = ComplexityComplexity
Verifiable inthe limit
Verifiable inthe limit
Refutable in the limit
Refutable in the limit
Decidablewith certainty
Decidablewith certainty
Decidable inthe limit
Decidable inthe limit
Verifiablewith certainty
Verifiablewith certainty
Refutablewith certainty
Refutablewith certainty
AE EA
AE
•The coin is fair•Computability•Catastrophism
•The coin is unfair•Uncomputability
•Uniformitarianism
•Universal laws•Existence claims
•It will rain tomorrowclopen/recursive
Refinement: RetractionsRefinement: Retractions
You are a fool not to invest in technology
0 1 1 0 ? 1 1 ? ? ? ? ?0 1 1 0 ? 1 1 ? ? ? ? ?NASDAQ
Retractions
Expansions
2 retractionsstarting with 0
2 retractionsstarting with 0
2 retractionsstarting with 1
2 retractionsstarting with 1
0 retractionsstarting with ?
0 retractionsstarting with ?
1 retractionstarting with ?
1 retractionstarting with ?
1 retractionstarting with 0
1 retractionstarting with 0
1 retractionstarting with 1
1 retractionstarting with 1
A E E A
AE
•Exactly n…
v
v
Verifiable inthe limit
Verifiable inthe limit
Refutable in the limit
Refutable in the limit
Decidable inthe limit
Decidable inthe limit
AE EA
= refutability with certainty
= verifiabilitywith certainty
= decidabilitywith certainty
. . .
Boolean combinations
of universals and existentials
Retractions Retractions asas
Complexity Complexity RefinementRefinement
Standard ObjectionStandard Objection
Very nice, but every method is reliable only under background presuppositions.
How do we know that the background assumptions are true?
Every assumption should be subject to empirical review.
Plausible FallacyPlausible Fallacy
If you could learn whether your pressupositions were true, you could chain this ability together with your original method to learn without them.
Therefore, if you need the presuppositions, you can’t reliably assess them.
Therefore, learning theory is an inadmissible version of foundationalism.
A Learnability AnalysisA Learnability Analysisof Methodological Regressof Methodological Regress
Presupposition of M =the set of worlds in which M succeeds.
MMH
successpresupposition
wor
lds
data
conj
ectu
res
No Free Lunch PrincipleNo Free Lunch Principle
The instrumental value of a regress is no greater than the best single-method performance that could be recovered from it without looking at the data.
…
Regress achievement
Scale of underdetermination
Single-method achievement
Empirical ConversionEmpirical Conversion An empirical conversion is a method that
produces conjectures solely on the basis of the conjectures of the given methods.
M1M1
H
M2M2
P1
M3M3
P2
MM
Methodological EquivalenceMethodological Equivalence
Reduction: B < A iffThere is an empirical conversion of an arbitrary group
of methods collectively achieving A into a group of methods collectively achieving B.
Methodological equivalence = inter-reducibility.
Simple IllustrationSimple Illustration
P1 is the presupposition under which M1 refutes H with certainty.
M2 refutes P1 with certainty.
M1M1
H
M2M2
P1
Worthless RegressWorthless Regress
M1 alternates mindlessly between acceptance and rejection.
M2 always rejects a priori.
PretensePretense
M pretends to refute H with certainty iff M never retracts a rejection.
•Duhem: no hypothesis is refutable in isolation.•Popper: to avoid coddling a false hypothesis forever, establish rejection conditions in advance even though the hypothesis is not really refutable.
Modified ExampleModified Example
Same as before But now M1 pretends to refute H with certainty.
M1M1
H
M2M2
P1
ReductionReduction
MReject when just one rejects
Accept otherwise
H
M1 ? ? ? 1 0 0 0 0 0
M2 ? 1 1 1 1 1 1 0 0
M 1 1 1 1 0 0 0 1 1
2 retractions in worst caseStarts not rejecting
ReliabilityReliability
H -H
P1
M1 never rejects
M2 never rejects
M1 rejects
M2 never rejects
-P1
M1 rejects
M2 rejects
M1 never rejects
M2 rejects
MReject when just one rejects
Accept otherwise
H
Converse ReductionConverse Reduction
M decides H with at most 3 retractions starting with acceptance.
Choose:– P1 = “M retracts at most once”
– M1 accepts until M uses one retraction and rejects thereafter.
– M2 accepts until M retracts twice and rejects thereafter.
Both methods pretend to refute.
ReliabilityReliability
Retractions
used by M0 1 2
H true false true
M1 never rejects rejects rejects
M2 never rejects never rejects rejects
P1 true true false
Regress TamedRegress Tamed
M1M1
H
M2M2
P1
Refutes with certainty
M1M1
H
2 retractionsstarting with 1
Complexityclassification
Pretends torefute with
certainty
regress method
Finite Regresses TamedFinite Regresses Tamed
M1M1
P0
M2M2
P1
Mk+1Mk+1
P2
. . .Pn
M
P0
Pretends : n1 retractionsstarting with c1
Pretends : n2 retractionsstarting with c2
n2 retractions
starting with c2
Sum all the retractions.Start with 1 if an even number of the regressmethods start with 0.
H
Infinite Popperian RegressesInfinite Popperian Regresses
M1M1
P0
M2M2
P1
Mk+1Mk+1
P2
. . .
. . .Pn
Pn + 1
M
P0
UI
UI
UI
Refutes with certaintyover UiPi
Each pretends to refute
with certainty
Ever weaker presuppositions
UI
ExampleExample
Gru
e 1
Gru
e 2
Gru
e 3
Gru
e 4
Gru
e 5
Gru
e 0
P0
P1P2 P3
. . .
Green
M1M1
P0
Halt after 2and projectfinal obs.
MiMi
Pi-1
Halt after 2iand projectfinal obs.
Regress of deciders:“2 more = forever”
K
ExampleExample
M
1 if only green emeralds have been seen.
0 otherwise
Gru
e 1
Gru
e 2
Gru
e 3
Gru
e 4
Gru
e 5
Gru
e 0 K
P0
P0
Green
Equivalent single refuting method
H
Other Infinite RegressesOther Infinite Regresses
M1M1
P0
M2M2
P1
Mk+1Mk+1
P2
. . .
. . .
Pn
Pn+1
M
P0
UI
UI
UIRefutes
in the limitover UiPi
Each pretends to Verify with certaintyUse bounded retractionsDecide in the limitRefute in the limit
Ever weaker presuppositions
UI
Example: UniformitariansmExample: UniformitariansmMichael Ruse, Michael Ruse, The Darwinian RevolutionThe Darwinian Revolution
Uniformitarianism (steady-state)
Catastrophism (progressive):
Com
plex
ity
Com
plex
ity
Stonesfield mammals
creation
Example: UniformitariansmExample: UniformitariansmMichael Ruse, Michael Ruse, The Darwinian RevolutionThe Darwinian Revolution
M1M1
P0
MiMi
Pi-1
Regress of 2-retractors equivalent to a single limiting refuter:
Halt with acceptance when surprised by early complexity.
Keep rejecting until then.
Accept before the ith surprise is encountered.
Reject when the ith surprise is encountered.
Accept and halt when the i+1th surprise is encountered.
Pi = any number of surprises except i.
H
Verifiable inthe limit
Verifiable inthe limit
Refutable in the limit
Refutable in the limit
Decidable withcertainty
Decidable withcertainty
Decidable inthe limit
Decidable inthe limit
Verifiable withcertainty
Verifiable withcertainty
Refutable withcertainty
Refutable withcertainty
AE
Gradualrefutability
Gradualrefutability
Gradual verifiability
Gradual verifiability
AE EA
The PowerThe Powerof of
NestedNestedInfiniteInfinite
EmpiricalEmpiricalRegressesRegresses
AEAEAE
Similar results
Naturalism LogicizedNaturalism Logicized
Unlimited Fallibilism: every presupposition is held up to the tribunal of experience.
No free lunch: captures objective power of empirical regresses.
Progress-oriented: convergence is the goal. Feasibility: reductions are computable, so analysis
applies to computable regresses. Historicism: dovetails with a logical viewpoint on
paradigms and articulations.