2015 30th Annual ACM/IEEE Symposium on Logic in Computer Science 2015
DOI: 10.1109/lics.2015.68
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Characterising Choiceless Polynomial Time with First-Order Interpretations

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Cited by 9 publications
(9 citation statements)
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“…We generalise this result to the case of counting and show that CPT-programs which decide the CFI query over complete graphs have to use set-like objects. In particular, this yields an interesting lower bound for a fragment of Interpretation Logic, a characterisation of Choiceless Polynomial Time which was presented in [12]: Interpretation Logic without congruences cannot decide the Cai-Fürer-Immerman query over complete graphs, and is thus strictly less expressive than the fragment of CPT using only sets of bounded rank.…”
Section: :4mentioning
confidence: 97%
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“…We generalise this result to the case of counting and show that CPT-programs which decide the CFI query over complete graphs have to use set-like objects. In particular, this yields an interesting lower bound for a fragment of Interpretation Logic, a characterisation of Choiceless Polynomial Time which was presented in [12]: Interpretation Logic without congruences cannot decide the Cai-Fürer-Immerman query over complete graphs, and is thus strictly less expressive than the fragment of CPT using only sets of bounded rank.…”
Section: :4mentioning
confidence: 97%
“…Interpretation Logic, which was introduced in [12], characterises CPT and some of its fragments in terms of first-order interpretations (with the Härtig quantifier for equicardinality testing). This framework allows to iterate a first-order interpretation until a first-order halting condition is satisfied, and evaluates a first-order sentence on the resulting structure (for details, see [12]), with polynomial bounds on the number of iterations and the size of the intermediate structures. The fragment of interpretation logic that arises when only interpretations without congruences are allowed, i.e.…”
Section: :16mentioning
confidence: 99%
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“…In this section we translate a CPT+WSC formula into an equivalent polynomial time DeepWL+WSC-algorithm. The following translation is based on the translation of CPT into interpretation logic in [14] and the translation of interpretation logic in DeepWL in [18]. However, we avoid the route through interpretation logic by directly implementing the ideas of [14] in DeepWL+WSC.…”
Section: From Cpt+wsc To Deepwl+wscmentioning
confidence: 99%
“…For the original definition of CPT by Blass, Gurevich and Shelah, see [2]. More usable formulations of CPT are for example BGS-logic [17] and polynomial interpretation logic (see [9], [18]).…”
Section: Choiceless Polynomial Timementioning
confidence: 99%