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1 #+TITLE: Categorification of Plausible Reasoning
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2 #+AUTHOR: Dylan Holmes
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3 #+MATHJAX: align:"left" mathml:t path:"../MathJax/MathJax.js"
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4 * COMMENT #+OPTIONS: LaTeX:dvipng
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5
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6 * Deductive and inductive posets
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7
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8 ** Definition
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9 If you have a collection \(P\) of logical propositions, you can order them by
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10 implication: \(a\) precedes \(b\) if and only if \(a\) implies
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11 \(b\). This makes \(P\) into a poset. Since the ordering arose from
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12 deductive implication, we'll call this a /deductive poset/.
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13
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14 If you have a deductive poset \(P\), you can create a related poset \(P^*\)
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15 as follows: the underlying set is the same, and for any two
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16 propositions \(a\) and \(b\) in \(P\), \(a\) precedes
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17 \(ab\) in \(P^*\). We'll call this an /inductive poset/.
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18
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19 ** A canonical map from deductive posets to inductive posets
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20 Each poset corresponds with a poset-category, that is a category with
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21 at most one arrow between any two objects. Considered as categories,
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22 inductive and deuctive posets are related as follows: there is a map
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23 \(\mathscr{F}\) which sends each arrow \(a\rightarrow b\) in \(P\) to
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24 the arrow \(a\rightarrow ab\) in \(P^*\). In fact, since \(a\) implies
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25 \(b\) if and only if \(a = ab\), \(\mathscr{F}\) sends each arrow in \(P\) to
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26 an identity arrow in \(P^*\) (specifically, it sends the arrow
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27 \(a\rightarrow b\) to the identity arrow \(a\rightarrow a\)).
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28
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29
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30 ** Assigning plausibilities to inductive posets
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31
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32 Inductive posets encode the relative (/qualitative/) plausibilities of its
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33 propositions: there exists an arrow \(x\rightarrow y\) only if \(x\)
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34 is at least as plausible as \(y\).
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35
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36 *** Consistent reasoning as a commutative diagram
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37 Inductive categories enable the following neat trick: we can interpret
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38 the objects of \(P^*\) as states of given information and interpret
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39 each arrow \(a\rightarrow ab\) in \(P^*\) as an inductive inference: the arrow
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40 \(a\rightarrow ab\) represents an inferential leap from the state of
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41 knowledge where only \(a\) is given to the state of knowledge where
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42 both \(a\) and \(b\) are given\mdash{} in this way, it represents
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43 the process of inferring \(b\) when given \(a\), and we label the
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44 arrow with \((b|a)\).
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45
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46 This trick has several important features that suggest its usefulness,
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47 namely
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48 - Composition of arrows corresponds to compound inference.
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49 - In the special case of deductive inference, the inferential arrow is an
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50 identity; the source and destination states of knowledge are the same.
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51 - One aspect of the consistency requirement of Jaynes[fn:1] takes the form of a
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52 commutative square: \(x\rightarrow ax \rightarrow abx\) =
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53 \(x\rightarrow bx \rightarrow abx\) is the categorified version of
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54 \((AB|X)=(A|X)\cdot(B|AX)=(B|X)\cdot(A|BX)\).
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55 - We can make plausibility assignments by enriching the inductive
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56 category \(P^*\) over some monoidal category, e.g. the set of real numbers
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57 (considered as a category) with its usual multiplication. /When we do/,
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58 the identity arrows of \(P^*\) \mdash{}corresponding to
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59 deductive inferences\mdash{} are assigned a value of certainty automatically.
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60
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61 [fn:1] /(IIIa) If a conclusion can be reasoned out in more than one
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62 way, then every possible way must lead to the same result./
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63
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64
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65 *** Reciprocal probabilities
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66 The natural numbers have a comparatively concrete origin: they are the
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67 result of decategorifying the category of finite sets[fn:2], or the
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68 coequalizer of the arrows from a one-object category to a two-object
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69 category with a single nonidentity arrow. Extensions of the set of
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70 natural numbers\mdash{} such as
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71 the set of integers or rational numbers or real numbers\mdash{} strike
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72 me as being somewhat more abstract.
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73
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74 Jaynes points out that our existing choice of scale for probabilities
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75 (i.e., the scale from 0 for impossibility to 1 for
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76 certainty) has a degree of freedom: any monotonic function of
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77 probability encodes the same information that probability does.
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78
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79 With this in mind, it seems useful to use not /probability/ but
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80 /reciprocal probability/ instead. This scale, which we might
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81 tentatively call freeness, is a scale ranging 1 (certainty) to
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82 positive infinity (impossibility).
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83
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84 In this way, the ``probability''
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85 associated with choosing one out of \(n\) indistinguishable choices
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86 becomes identified with \(n\).
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87
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88 The entropy
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89
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90 [fn:2] As Baez says.
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91
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92
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93
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94 ** self-questions
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95
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96 What circumstances would make \(\mathscr{F}\) an injection?
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97
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98 What if \(P=\{\top,\bot\}\)?
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99
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100
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101
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102 ** COMMENT
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103 Inductive and deductive posets are related as follows: there is a monotone
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104 inclusion map \(\mathscr{i}:P^*\hookrightarrow P\) which\mdash{} since \(a\)
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105 implies \(b\) is equivalent to \(a=ab\)\mdash{} sends comparable
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106 propositions in \(P\) to the same proposition in \(P^*\). Conversely,
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107 only comparable propositions in \(P\) are sent to the same proposition
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108 in \(P^*\).
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109
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110
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111
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112 ** Inductive posets and plausibility
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113
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114 * Inverse Probability
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