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Model Theoretical Aspects of Weakly Aggregative Modal Logic

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Abstract

Weakly Aggregative Modal Logic (\(\textsf {WAML}\)) is a collection of disguised polyadic modal logics with n-ary modalities whose arguments are all the same. \(\textsf {WAML}\) has interesting applications on epistemic logic, deontic logic, and the logic of belief. In this paper, we study some basic model theoretical aspects of \(\textsf {WAML}\). Specifically, we first give a van Benthem–Rosen characterization theorem of \(\textsf {WAML}\) based on an intuitive notion of bisimulation. Then, in contrast to many well known normal or non-normal modal logics, we show that each basic \(\textsf {WAML}\) system \({\mathbb {K}}_n\) lacks Craig interpolation. Finally, by model theoretical techniques, we show that an extension of \({\mathbb {K}}_2\) does have Craig interpolation, as an example of amending the interpolation problem of \(\textsf {WAML}\).

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Notes

  1. This is not to be confused with the non-contingency operator, which is also denoted as \(\nabla \) in non-contingency or knowing whether logics (Fan et al. 2015).

  2. One can find a model theoretical survey on \(\textsf {PML}\) in Liu (2019).

  3. Name mentioned by Yde Venema via personal communications.

  4. It is worth noting that the parameter n appears only in the semantics and not in the syntax. This suggests a natural generalization of the semantics where we drop the requirement that all successor tuples are of the same length; they do not even need to be tuples, since how worlds are ordered in those tuples is also not important. The resulting semantics is then based on hypergraphs. See Ding et al. (2021) and Nicholson (2009) for developments along this line.

  5. Other connections between WAML and graph coloring problems can be found in Nicholson and Allen (2003), where the four-color problem is coded by the validity of some rules in the WAML language.

  6. We include the propositional constant \(\top \) here because otherwise logics in this language trivially cannot have the Craig Interpolation Property.

  7. The rule \(\mathtt {N}\) can be replaced by the axiom \(\Box \top \) since we have \(\mathtt {RM}\) here.

  8. An infinitary proof for the Characterization Theorem over arbitrary n-models using \(\omega \)-saturated ultrapowers is also possible. but due to the space limit we only present the proof which also works for finite models.

  9. To avoid too many subscripts, we use square brackets to index vectors: for any tuple \(\vec {v}\) of length n and natural number i such that \(1 \le i \le n\), \(\vec {v}[i]\) is the i’th element of \(\vec {v}\).

  10. See Libkin (2013, Chap 4), for a thorough introduction to Gaifman graph and related results, though we do not rely on any of them in this paper; the graph is introduced only to define the distance function.

  11. In textbooks such as Libkin (2013) using Gaifman graphs, the distance to be preserved is usually \(3^{q-m}\) instead of \(2^{q-m}\). However, in the literature of modal logic, the \(2^{q-m}\) bound is more common (see Goranko et al. 2007 for example), and even in a general setting in first-order logic, an \(O(2^n)\) bound is achievable. See Exercise 4.10 of Libkin (2013).

  12. A formula \(\varphi \) is rank-1 if all propositional letters occur in the scope of exactly 1 modal operator. A rank-1 monotone logic is the smallest set of formulas containing a set of rank-1 formulas and all propositional tautologies and is closed under the rules RM, modus ponens, and uniform substitution.

  13. Let \(P_1\) and \(P_2\) be the two parts and assume that \(n > 2\). Then for each \(u \in P_1\) pick an edge \(e_u\) covering u and thus forming a function \(f: P_1 \rightarrow P_2\) such that f(u) is the vertex of \(e_u\) in \(P_2\). If the range of f has more than 1 vertex so that \(|P_2 {\setminus } {\textit{range}}(f)| \le n-2\), then we are done as we just need to pick one edge for each one in \(P_2 {\setminus } {\textit{range}}(f)\), resulting in a total of at most \(2n-2\) edges. If \({\textit{range}}(f)\) is a singleton, say \(\{b_1\}\), we still pick for each \(v \in P_2 {\setminus } \{b_1\}\) an edge \(e_v\) covering v and thus forming similarly a function \(g:P_2{\setminus } \{b_1\} \rightarrow P_1\) such that g(v) is the vertex of \(e_v\) in \(P_1\). Now we may have picked \(2n-1\) edges. However, pick \(b_2 \in P_2 {\setminus } \{b_1\}\), and then we can omit the edge \(e_{g(b_2)}\) we picked. This is because the two vertices \(e_{g(b_2)}\) covers, namely \(g(b_2)\) and \(b_1\), are both covered by other edges. \(g(b_2)\) of course is covered by \(e_{b_2}\). \(b_1\) is covered by \(e_u\) for any \(u \in P_1 {\setminus } \{g(b_2)\}\). Hence we still need no more than \(2n-2\) edges.

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Correspondence to Yifeng Ding.

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This paper is an extended journal version of  Liu et al. (2019). In this extended version, a detailed proof of Theorem 2 is provided using updated techniques, and a new result on recovering Craig interpolation (Theorem 6) is added. Jixin Liu thanks China Postdoctoral Science Foundation (2020M683344) and Fundamental Research Funds of SCU (2021-Philosophy-02) for support. Yanjing Wang gratefully acknowledges the support from NSSF (Grant 19BZX135).

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Liu, J., Ding, Y. & Wang, Y. Model Theoretical Aspects of Weakly Aggregative Modal Logic. J of Log Lang and Inf 31, 261–286 (2022). https://doi.org/10.1007/s10849-022-09366-x

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