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All the ideas for 'The Evolution of Logic', 'works' and 'Inference to the Best Explanation (2nd)'

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102 ideas

1. Philosophy / C. History of Philosophy / 4. Later European Philosophy / c. Eighteenth century philosophy
We are all post-Kantians, because he set the current agenda for philosophy [Hart,WD]
1. Philosophy / D. Nature of Philosophy / 5. Aims of Philosophy / d. Philosophy as puzzles
The problems are the monuments of philosophy [Hart,WD]
1. Philosophy / F. Analytic Philosophy / 6. Logical Analysis
To study abstract problems, some knowledge of set theory is essential [Hart,WD]
2. Reason / A. Nature of Reason / 4. Aims of Reason
Good inference has mechanism, precision, scope, simplicity, fertility and background fit [Lipton]
2. Reason / B. Laws of Thought / 4. Contraries
Contrary pairs entail contradictions; one member entails negation of the other [Lipton]
2. Reason / D. Definition / 1. Definitions
Definition just needs negation, known variables, conjunction, disjunction, substitution and quantification [Weyl, by Lavine]
3. Truth / C. Correspondence Truth / 2. Correspondence to Facts
Tarski showed how we could have a correspondence theory of truth, without using 'facts' [Hart,WD]
3. Truth / F. Semantic Truth / 1. Tarski's Truth / b. Satisfaction and truth
Truth for sentences is satisfaction of formulae; for sentences, either all sequences satisfy it (true) or none do [Hart,WD]
3. Truth / F. Semantic Truth / 2. Semantic Truth
A first-order language has an infinity of T-sentences, which cannot add up to a definition of truth [Hart,WD]
4. Formal Logic / B. Propositional Logic PL / 2. Tools of Propositional Logic / c. Derivation rules of PL
Conditional Proof: infer a conditional, if the consequent can be deduced from the antecedent [Hart,WD]
4. Formal Logic / C. Predicate Calculus PC / 2. Tools of Predicate Calculus / e. Existential quantifier ∃
∃y... is read as 'There exists an individual, call it y, such that...', and not 'There exists a y such that...' [Hart,WD]
4. Formal Logic / F. Set Theory ST / 1. Set Theory
Set theory articulates the concept of order (through relations) [Hart,WD]
Nowadays ZFC and NBG are the set theories; types are dead, and NF is only useful for the whole universe [Hart,WD]
4. Formal Logic / F. Set Theory ST / 2. Mechanics of Set Theory / a. Symbols of ST
∈ relates across layers, while ⊆ relates within layers [Hart,WD]
4. Formal Logic / F. Set Theory ST / 3. Types of Set / b. Empty (Null) Set
Without the empty set we could not form a∩b without checking that a and b meet [Hart,WD]
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / i. Axiom of Foundation VIII
In the modern view, foundation is the heart of the way to do set theory [Hart,WD]
Foundation Axiom: an nonempty set has a member disjoint from it [Hart,WD]
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / j. Axiom of Choice IX
We can choose from finite and evident sets, but not from infinite opaque ones [Hart,WD]
With the Axiom of Choice every set can be well-ordered [Hart,WD]
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / o. Axiom of Constructibility V = L
If we accept that V=L, it seems to settle all the open questions of set theory [Hart,WD]
4. Formal Logic / F. Set Theory ST / 5. Conceptions of Set / d. Naïve logical sets
Naïve set theory has trouble with comprehension, the claim that every predicate has an extension [Hart,WD]
4. Formal Logic / F. Set Theory ST / 5. Conceptions of Set / e. Iterative sets
The iterative conception may not be necessary, and may have fixed points or infinitely descending chains [Hart,WD]
4. Formal Logic / F. Set Theory ST / 6. Ordering in Sets
A 'partial ordering' is irreflexive and transitive; the sets are ordered, but not the subsets [Hart,WD]
A partial ordering becomes 'total' if any two members of its field are comparable [Hart,WD]
'Well-ordering' must have a least member, so it does the natural numbers but not the integers [Hart,WD]
Von Neumann defines α<β as α∈β [Hart,WD]
4. Formal Logic / F. Set Theory ST / 8. Critique of Set Theory
Maybe sets should be rethought in terms of the even more basic categories [Hart,WD]
5. Theory of Logic / G. Quantification / 3. Objectual Quantification
The universal quantifier can't really mean 'all', because there is no universal set [Hart,WD]
5. Theory of Logic / J. Model Theory in Logic / 1. Logical Models
Modern model theory begins with the proof of Los's Conjecture in 1962 [Hart,WD]
Model theory studies how set theory can model sets of sentences [Hart,WD]
Model theory is mostly confined to first-order theories [Hart,WD]
Models are ways the world might be from a first-order point of view [Hart,WD]
5. Theory of Logic / K. Features of Logics / 6. Compactness
First-order logic is 'compact': consequences of a set are consequences of a finite subset [Hart,WD]
5. Theory of Logic / L. Paradox / 4. Paradoxes in Logic / c. Berry's paradox
Berry's Paradox: we succeed in referring to a number, with a term which says we can't do that [Hart,WD]
5. Theory of Logic / L. Paradox / 5. Paradoxes in Set Theory / c. Burali-Forti's paradox
The Burali-Forti paradox is a crisis for Cantor's ordinals [Hart,WD]
5. Theory of Logic / L. Paradox / 6. Paradoxes in Language / a. The Liar paradox
The machinery used to solve the Liar can be rejigged to produce a new Liar [Hart,WD]
6. Mathematics / A. Nature of Mathematics / 3. Nature of Numbers / e. Ordinal numbers
The less-than relation < well-orders, and partially orders, and totally orders the ordinal numbers [Hart,WD]
The axiom of infinity with separation gives a least limit ordinal ω [Hart,WD]
There are at least as many infinite cardinals as transfinite ordinals (because they will map) [Hart,WD]
Von Neumann's ordinals generalise into the transfinite better, because Zermelo's ω is a singleton [Hart,WD]
6. Mathematics / A. Nature of Mathematics / 3. Nature of Numbers / g. Real numbers
19th century arithmetization of analysis isolated the real numbers from geometry [Hart,WD]
6. Mathematics / A. Nature of Mathematics / 5. The Infinite / a. The Infinite
We can establish truths about infinite numbers by means of induction [Hart,WD]
6. Mathematics / B. Foundations for Mathematics / 3. Axioms for Geometry
Euclid has a unique parallel, spherical geometry has none, and saddle geometry has several [Hart,WD]
6. Mathematics / C. Sources of Mathematics / 6. Logicism / d. Logicism critique
Mathematics makes existence claims, but philosophers usually say those are never analytic [Hart,WD]
7. Existence / C. Structure of Existence / 8. Stuff / a. Pure stuff
Mass words do not have plurals, or numerical adjectives, or use 'fewer' [Hart,WD]
11. Knowledge Aims / A. Knowledge / 2. Understanding
Understanding is not mysterious - it is just more knowledge, of causes [Lipton]
12. Knowledge Sources / A. A Priori Knowledge / 2. Self-Evidence
Fregean self-evidence is an intrinsic property of basic truths, rules and definitions [Hart,WD]
12. Knowledge Sources / A. A Priori Knowledge / 11. Denying the A Priori
The failure of key assumptions in geometry, mereology and set theory throw doubt on the a priori [Hart,WD]
13. Knowledge Criteria / B. Internal Justification / 3. Evidentialism / a. Evidence
How do we distinguish negative from irrelevant evidence, if both match the hypothesis? [Lipton]
14. Science / A. Basis of Science / 1. Observation
The inference to observables and unobservables is almost the same, so why distinguish them? [Lipton]
14. Science / A. Basis of Science / 2. Demonstration
Inductive inference is not proof, but weighing evidence and probability [Lipton]
We infer from evidence by working out what would explain that evidence [Lipton]
14. Science / A. Basis of Science / 4. Prediction
It is more impressive that relativity predicted Mercury's orbit than if it had accommodated it [Lipton]
Predictions are best for finding explanations, because mere accommodations can be fudged [Lipton]
14. Science / B. Scientific Theories / 1. Scientific Theory
If we make a hypothesis about data, then a deduction, where does the hypothesis come from? [Lipton]
14. Science / C. Induction / 1. Induction
Induction is repetition, instances, deduction, probability or causation [Lipton]
14. Science / C. Induction / 3. Limits of Induction
Standard induction does not allow for vertical inferences, to some unobservable lower level [Lipton]
14. Science / C. Induction / 4. Reason in Induction
An inductive inference is underdetermined, by definition [Lipton]
We can argue to support our beliefs, so induction will support induction, for believers in induction [Lipton]
14. Science / C. Induction / 5. Paradoxes of Induction / b. Raven paradox
If something in ravens makes them black, it may be essential (definitive of ravens) [Lipton]
My shoes are not white because they lack some black essence of ravens [Lipton]
A theory may explain the blackness of a raven, but say nothing about the whiteness of shoes [Lipton]
We can't turn non-black non-ravens into ravens, to test the theory [Lipton]
To pick a suitable contrast to ravens, we need a hypothesis about their genes [Lipton]
14. Science / C. Induction / 6. Bayes's Theorem
Bayes seems to rule out prior evidence, since that has a probability of one [Lipton]
A hypothesis is confirmed if an unlikely prediction comes true [Lipton]
Bayes involves 'prior' probabilities, 'likelihood', 'posterior' probability, and 'conditionalising' [Lipton]
Explanation may be an important part of implementing Bayes's Theorem [Lipton]
Bayes is too liberal, since any logical consequence of a hypothesis confirms it [Lipton]
14. Science / D. Explanation / 1. Explanation / a. Explanation
Explanation may describe induction, but may not show how it justifies, or leads to truth [Lipton]
14. Science / D. Explanation / 1. Explanation / b. Aims of explanation
An explanation gives the reason the phenomenon occurred [Lipton]
An explanation is what makes the unfamiliar familiar to us [Lipton]
An explanation is what is added to knowledge to yield understanding [Lipton]
Seaching for explanations is a good way to discover the structure of the world [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / b. Contrastive explanations
In 'contrastive' explanation there is a fact and a foil - why that fact, rather than this foil? [Lipton]
With too many causes, find a suitable 'foil' for contrast, and the field narrows right down [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / c. Explanations by coherence
An explanation unifies a phenomenon with our account of other phenomena [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / e. Lawlike explanations
Deduction explanation is too easy; any law at all will imply the facts - together with the facts! [Lipton]
We reject deductive explanations if they don't explain, not if the deduction is bad [Lipton]
Good explanations may involve no laws and no deductions [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / f. Necessity in explanations
An explanation shows why it was necessary that the effect occurred [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / g. Causal explanations
A cause may not be an explanation [Lipton]
To explain is to give either the causal history, or the causal mechanism [Lipton]
Mathematical and philosophical explanations are not causal [Lipton]
Explanations may be easier to find than causes [Lipton]
Causal inferences are clearest when we can manipulate things [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / i. Explanations by mechanism
We want to know not just the cause, but how the cause operated [Lipton]
14. Science / D. Explanation / 2. Types of Explanation / l. Probabilistic explanations
To maximise probability, don't go beyond your data [Lipton]
14. Science / D. Explanation / 3. Best Explanation / a. Best explanation
Is Inference to the Best Explanation nothing more than inferring the likeliest cause? [Lipton]
Best Explanation as a guide to inference is preferable to best standard explanations [Lipton]
The 'likeliest' explanation is the best supported; the 'loveliest' gives the most understanding [Lipton]
IBE is inferring that the best potential explanation is the actual explanation [Lipton]
Finding the 'loveliest' potential explanation links truth to understanding [Lipton]
IBE is not passive treatment of data, but involves feedback between theory and data search [Lipton]
A contrasting difference is the cause if it offers the best explanation [Lipton]
We select possible explanations for explanatory reasons, as well as choosing among them [Lipton]
14. Science / D. Explanation / 3. Best Explanation / c. Against best explanation
Must we only have one explanation, and must all the data be made relevant? [Lipton]
Bayesians say best explanations build up an incoherent overall position [Lipton]
The best theory is boring: compare 'all planets move elliptically' with 'most of them do' [Lipton]
Best explanation can't be a guide to truth, because the truth must precede explanation [Lipton]
18. Thought / D. Concepts / 3. Ontology of Concepts / c. Fregean concepts
The Fregean concept of GREEN is a function assigning true to green things, and false to the rest [Hart,WD]
26. Natural Theory / C. Causation / 9. General Causation / c. Counterfactual causation
Counterfactual causation makes causes necessary but not sufficient [Lipton]