77 ideas
| 19306 | It is a principle of reasoning not to clutter your mind with trivialities [Harman] |
| 19304 | The rules of reasoning are not the rules of logic [Harman] |
| 19307 | If there is a great cost to avoiding inconsistency, we learn to reason our way around it [Harman] |
| 19309 | Logic has little relevance to reasoning, except when logical conclusions are immediate [Harman] |
| 19303 | Implication just accumulates conclusions, but inference may also revise our views [Harman] |
| 16841 | Good inference has mechanism, precision, scope, simplicity, fertility and background fit [Lipton] |
| 16854 | Contrary pairs entail contradictions; one member entails negation of the other [Lipton] |
| 13030 | Extensionality: ∀x ∀y (∀z (z ∈ x ↔ z ∈ y) → x = y) [Kunen] |
| 13032 | Pairing: ∀x ∀y ∃z (x ∈ z ∧ y ∈ z) [Kunen] |
| 13033 | Union: ∀F ∃A ∀Y ∀x (x ∈ Y ∧ Y ∈ F → x ∈ A) [Kunen] |
| 13037 | Infinity: ∃x (0 ∈ x ∧ ∀y ∈ x (S(y) ∈ x) [Kunen] |
| 13038 | Power Set: ∀x ∃y ∀z(z ⊂ x → z ∈ y) [Kunen] |
| 13034 | Replacement: ∀x∈A ∃!y φ(x,y) → ∃Y ∀X∈A ∃y∈Y φ(x,y) [Kunen] |
| 13039 | Foundation:∀x(∃y(y∈x) → ∃y(y∈x ∧ ¬∃z(z∈x ∧ z∈y))) [Kunen] |
| 13036 | Choice: ∀A ∃R (R well-orders A) [Kunen] |
| 13029 | Set Existence: ∃x (x = x) [Kunen] |
| 13031 | Comprehension: ∃y ∀x (x ∈ y ↔ x ∈ z ∧ φ) [Kunen] |
| 13040 | Constructibility: V = L (all sets are constructible) [Kunen] |
| 19305 | The Gambler's Fallacy (ten blacks, so red is due) overemphasises the early part of a sequence [Harman] |
| 19310 | High probability premises need not imply high probability conclusions [Harman] |
| 16814 | Understanding is not mysterious - it is just more knowledge, of causes [Lipton] |
| 19308 | We strongly desire to believe what is true, even though logic does not require it [Harman] |
| 16825 | How do we distinguish negative from irrelevant evidence, if both match the hypothesis? [Lipton] |
| 19311 | In revision of belief, we need to keep track of justifications for foundations, but not for coherence [Harman] |
| 19312 | Coherence is intelligible connections, especially one element explaining another [Harman] |
| 16851 | The inference to observables and unobservables is almost the same, so why distinguish them? [Lipton] |
| 16799 | Inductive inference is not proof, but weighing evidence and probability [Lipton] |
| 16798 | We infer from evidence by working out what would explain that evidence [Lipton] |
| 16856 | It is more impressive that relativity predicted Mercury's orbit than if it had accommodated it [Lipton] |
| 16857 | Predictions are best for finding explanations, because mere accommodations can be fudged [Lipton] |
| 16827 | If we make a hypothesis about data, then a deduction, where does the hypothesis come from? [Lipton] |
| 16804 | Induction is repetition, instances, deduction, probability or causation [Lipton] |
| 16823 | Standard induction does not allow for vertical inferences, to some unobservable lower level [Lipton] |
| 16800 | An inductive inference is underdetermined, by definition [Lipton] |
| 16858 | We can argue to support our beliefs, so induction will support induction, for believers in induction [Lipton] |
| 16832 | If something in ravens makes them black, it may be essential (definitive of ravens) [Lipton] |
| 16836 | My shoes are not white because they lack some black essence of ravens [Lipton] |
| 16831 | A theory may explain the blackness of a raven, but say nothing about the whiteness of shoes [Lipton] |
| 16833 | We can't turn non-black non-ravens into ravens, to test the theory [Lipton] |
| 16834 | To pick a suitable contrast to ravens, we need a hypothesis about their genes [Lipton] |
| 16802 | Bayes seems to rule out prior evidence, since that has a probability of one [Lipton] |
| 16803 | Bayes is too liberal, since any logical consequence of a hypothesis confirms it [Lipton] |
| 16801 | A hypothesis is confirmed if an unlikely prediction comes true [Lipton] |
| 16837 | Bayes involves 'prior' probabilities, 'likelihood', 'posterior' probability, and 'conditionalising' [Lipton] |
| 16839 | Explanation may be an important part of implementing Bayes's Theorem [Lipton] |
| 16850 | Explanation may describe induction, but may not show how it justifies, or leads to truth [Lipton] |
| 16807 | An explanation gives the reason the phenomenon occurred [Lipton] |
| 16808 | An explanation is what makes the unfamiliar familiar to us [Lipton] |
| 16806 | An explanation is what is added to knowledge to yield understanding [Lipton] |
| 16822 | Seaching for explanations is a good way to discover the structure of the world [Lipton] |
| 16816 | In 'contrastive' explanation there is a fact and a foil - why that fact, rather than this foil? [Lipton] |
| 16826 | With too many causes, find a suitable 'foil' for contrast, and the field narrows right down [Lipton] |
| 16811 | An explanation unifies a phenomenon with our account of other phenomena [Lipton] |
| 16810 | Deduction explanation is too easy; any law at all will imply the facts - together with the facts! [Lipton] |
| 16829 | We reject deductive explanations if they don't explain, not if the deduction is bad [Lipton] |
| 16809 | Good explanations may involve no laws and no deductions [Lipton] |
| 16812 | An explanation shows why it was necessary that the effect occurred [Lipton] |
| 16846 | A cause may not be an explanation [Lipton] |
| 16813 | To explain is to give either the causal history, or the causal mechanism [Lipton] |
| 16815 | Mathematical and philosophical explanations are not causal [Lipton] |
| 16849 | Explanations may be easier to find than causes [Lipton] |
| 16848 | Causal inferences are clearest when we can manipulate things [Lipton] |
| 16842 | We want to know not just the cause, but how the cause operated [Lipton] |
| 16840 | To maximise probability, don't go beyond your data [Lipton] |
| 16824 | Is Inference to the Best Explanation nothing more than inferring the likeliest cause? [Lipton] |
| 16817 | Best Explanation as a guide to inference is preferable to best standard explanations [Lipton] |
| 16818 | The 'likeliest' explanation is the best supported; the 'loveliest' gives the most understanding [Lipton] |
| 16819 | IBE is inferring that the best potential explanation is the actual explanation [Lipton] |
| 16820 | Finding the 'loveliest' potential explanation links truth to understanding [Lipton] |
| 16828 | IBE is not passive treatment of data, but involves feedback between theory and data search [Lipton] |
| 16844 | A contrasting difference is the cause if it offers the best explanation [Lipton] |
| 16853 | We select possible explanations for explanatory reasons, as well as choosing among them [Lipton] |
| 16821 | Must we only have one explanation, and must all the data be made relevant? [Lipton] |
| 16838 | Bayesians say best explanations build up an incoherent overall position [Lipton] |
| 16855 | The best theory is boring: compare 'all planets move elliptically' with 'most of them do' [Lipton] |
| 16852 | Best explanation can't be a guide to truth, because the truth must precede explanation [Lipton] |
| 16847 | Counterfactual causation makes causes necessary but not sufficient [Lipton] |