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Putting the Building-Blocks Together

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Descriptor Revision

Part of the book series: Trends in Logic ((TREN,volume 46))

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Abstract

This is the first of four chapters that form the central part of the book, introducing and developing a new approach to belief change, descriptor revision. In this chapter, the new model is constructed from its basic components. We begin with a skeletal input-output model that contains no sentences but only primitive (i.e., unstructured) belief states and inputs, together with a revision function \(\circledcirc \) that takes us from any belief state \(\mathcal {K}\) and input \(\text {\i }\) to a new belief state \(\mathcal {K} \circledcirc \text {\i }\). This model has the advantage of making few controversial assumptions but also the disadvantage of low expressive power. It is used as a starting-point to which more structure is added successively, allowing us to see what assumptions are needed to obtain the resulting increase in expressive power. Sentences are added to the framework with the help of a support function that takes us from any belief state \(\mathcal {K}\) to the set of sentences representing the beliefs that it supports. After that, the two major components of the new framework are introduced. The first is belief descriptors, a versatile construct for describing belief states. The metalinguistic expression \(\mathfrak {B}p\) denotes that p is believed in the belief state under consideration. Truth-functional combinations are interpreted in the usual way, thus \(\lnot \mathfrak {B}p\) denotes that p is not believed and \(\mathfrak {B}p \vee \mathfrak {B}\lnot p\) that either p or \(\lnot p\) is believed. Sets of such expressions are used to denote combined properties, hence \(\{\lnot \mathfrak {B}p, \lnot \mathfrak {B}q\}\) denotes that neither p nor q is believed. Belief descriptors (either single sentences or sets of such sentences) are used as inputs for belief change (replacing primitive inputs such as \(\text {\i }\)). Due to their versatility, all changes can be performed with a single, uniform change operation \(\circ \). In order to revise the belief set K by a sentence p we use the input (success condition) \(\mathfrak {B}p\), and the outcome is \(K \circ \mathfrak {B}p\). In order to remove the sentence q we perform the operation \(K \circ \lnot \mathfrak {B}q\), etc. In order to perform these operations, the second major component of the new framework is introduced, namely a selection mechanism (a monoselective choice function) that directly selects the output from those among a given set of potential outcomes (the “outcome set”) that satisfy the success condition.

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Notes

  1. 1.

    And in other sentences containing the same information. The joint information content of sentences with the same meaning is called a proposition. All this could alternatively be expressed in terms of propositions.

  2. 2.

    In the terminology of automata theory it is a transition function.

  3. 3.

    Changes consisting of the drawing of new inferences from old information have been included in some belief change models; see [83, 91, pp. 20–21], [112, 204].

  4. 4.

    The symbol\(\check{}\)above the symbol representing a (deterministic) belief change operation will be used to denote the indeterministic generalization of that operation.

  5. 5.

    As noted by Hans Rott [223], this problem is not present in extended versions of the AGM model where the outcome of a contraction or revision is not just a belief set but a larger object that contains information about how additional changes will be performed.

  6. 6.

    More precisely: different belief states that generate inconsistencies in the language of the support function.

  7. 7.

    The same is true of belief base models in which the belief state is represented by a set of sentences that is not logically closed. Different such belief bases may have the same logical closure and therefore represent belief states with the same belief set [84, 88, 89, 94].

  8. 8.

    In addition, actual belief systems are capable of containing local inconsistencies that do not corrupt the entire belief system. It is “quite feasible to believe both that Jesus was a human being and that Jesus was not a human being, without believing that the moon is made of cheese” [139, p. 49]. To represent this feature we can employ a support function \(\mathfrak {s}\) that does not satisfy closure under classical consequence (but possibly some weaker, paraconsistent closure condition). On local inconsistencies, see [139].

  9. 9.

    The direct versions of these properties are discussed in [121].

  10. 10.

    Since \(p\in K*p\) and \(p\notin (K\div p)\setminus \text {Cn}(\varnothing )\).

  11. 11.

    It can be applied repeatedly, and can therefore equivalently be expressed as follows: If \(\mathfrak {s}(\mathcal {K}) = \mathfrak {s}(\mathcal {K}')\), then \(\mathfrak {s}(\mathcal {K}\circledcirc {\text {\i }}_1 \circledcirc {\dots } \circledcirc {\text {\i }}_n) = \mathfrak {s}(\mathcal {K}' \circledcirc {\text {\i }}_1 \circledcirc {\dots } \circledcirc {\text {\i }}_n)\) for all series \({\text {\i }}_1,{\dots },{\text {\i }}_n\) of elements of \(\mathbb {I}\).

  12. 12.

    On the difference between static and dynamic equivalence of belief states, see [83].

  13. 13.

    Suppose that an input \({\text {\i }}\) (1) strengthens p in \(\mathcal {K}\), but (2) does not move any sentence across the belief/non-belief border. It would seem to follow from (1) that there is some series \({\text {\i }}_1,{\dots },{\text {\i }}_n\) of inputs such that \(p\notin \mathfrak {s}(\mathcal {K}\circledcirc {\text {\i }}_1 \circledcirc {\dots } \circledcirc {\text {\i }}_n)\) and \(p\in \mathfrak {s}(\mathcal {K}\circledcirc {\text {\i }}\circledcirc {\text {\i }}_1 \circledcirc {\dots }\circledcirc {\text {\i }}_n)\), but it follows from (2) that \(\mathfrak {s}(\mathcal {K}\circledcirc {\text {\i }})=\mathfrak {s}(\mathcal {K})\). This contradicts sententiality. On operations that strengthen or weaken beliefs, see [28].

  14. 14.

    This is particularly pertinent if autoepistemic or conditional beliefs are included in the belief set. See Chapter 7.

  15. 15.

    Frank Ramsey noted in 1925 that “A believes p” is not a truth function of p but can instead be treated as “one of other atomic propositions”. [210, p. 9n].

  16. 16.

    Composite descriptors with one element will be used interchangeably with the molecular descriptor that they contain. For instance, \(\{\mathfrak {B}p\}\) and \(\mathfrak {B}p\) will be used interchangeably.

  17. 17.

    More precisely: It does not allow the formation of expressions in which an instance of \(\mathfrak {B}\) appears within the scope of another instance of \(\mathfrak {B}\).

  18. 18.

    This terminology is used in [107] and [239, p. 280]. It is based on the terminology for two types of multiple contraction used in [64]. Hans Rott uses the terms “bunch revision” and “pick revision” for the same concepts [217, p. 65].

  19. 19.

    To see that, let p and q be logically independent elements of \(\mathcal {L}\), and let \(\Psi =\{\mathfrak {B}p\}\) and \(\alpha =\mathfrak {B}q\).

  20. 20.

    A set of sentences is logically infinite if and only if it has infinitely many equivalence classes in terms of logical equivalence. Cf. Section 2.5.

  21. 21.

    This observation is related to the well-known theorem that a theory is equivalent to a Horn theory if and only if the set of its models is closed under intersection. This was proved (in a generalized form) in [187]. A more accessible proof can be found in [38, pp. 254–257], and an excellent introduction to Horn clauses in [148].

  22. 22.

    The term “descriptor revision” refers to operations that take descriptors as inputs. For clarity, the operations called “revision” in the traditional approach will be called “sentential revision”.

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Correspondence to Sven Ove Hansson .

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Hansson, S.O. (2017). Putting the Building-Blocks Together. In: Descriptor Revision. Trends in Logic, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-319-53061-1_4

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