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Improbability and Novelty of Descriptions

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Novelty, Information and Surprise
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Abstract

In this chapter we define the information of an event AΣ, or in our terminology the novelty of a propositionA as \({-\log }_{2}p(A)\). We further define the important new concept of a description and extend the definition of novelty from events to descriptions. Finally we introduce the notions of completeness and directedness of descriptions and thereby the distinction between surprise and information, which are opposite special cases of novelty.

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Notes

  1. 1.

    This definition is the classical basic definition of information or entropy, which goes back to Boltzmann (1887) (see also Brush 1966).

  2. 2.

    This requirement obviously implies that the propositions [d = A] are in Σ for every A ∈ R(d). It also implies that R(d) is finite or countable.

  3. 3.

    For example, one can describe points \(x \in A \setminus C\) by d(x) = A, points x in A ∩ C by d(x) = A ∩ C, points x in \(B \setminus C\) by d(x) = B, and points x in B ∩ C by d(x) = C.

  4. 4.

    From Definition (ii) it is obvious that the probability that ω is in two sets, e.g., A i and A j , is 0. So, disregarding propositions with probability 0, every ω ∈ Ω is in exactly one of the sets A i . We will usually disregard propositions with probability 0 and this is meant by the word “essentially”.

  5. 5.

    Due to the additional requirement in Definition 2.3 the function N d is measurable. However, it may happen that E(N d ) is infinite. For an example see Proposition 2.17.

  6. 6.

    Strictly speaking, here a partition should be defined by \({A}_{i} \cap {A}_{j} = \varnothing \) instead of \(p({A}_{i} \cap {A}_{j}) = 0\) (compare Definition  2.4). If we disregard 0-probability-propositions we should interpret \(d =\tilde{ d}\) in Definition  2.6 as \(p[d =\tilde{ d}] = 1\) and we should use the weaker formulation \(p(d(\omega ) \cap d(\omega ^{\prime})) = 0\) in part (ii) of this definition.

  7. 7.

    If \(p(\widetilde{A}) = 0\) for some \(\widetilde{A}\) in the range of \(\tilde{d}\), we set \(p(\widetilde{A})\log p(\widetilde{A}) = 0\) since \({\lim }_{x\rightarrow {0}^{+}}x\log x = 0\).

  8. 8.

    Here we rely on the approximation argument as in Sect. 1.3 for the calculation of an expectation value. If all the finite sum approximations satisfy the same inequality (\(\leq \frac{1} {\ln 2}\)), then this inequality is also satisfied by the limit.

  9. 9.

    See Definition 1.3.

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Palm, G. (2012). Improbability and Novelty of Descriptions. In: Novelty, Information and Surprise. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29075-6_2

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