Abstract
The probability logic denoted \(LPP_2\) is described with the aim to give a clear, step-by-step introduction to the field and the main proof techniques that will be used elsewhere in the book. The logic enriches propositional calculus with probabilistic operators of the form \(P_{\ge s}\) with the intended meaning “probability is at least s”. In \(LPP_2\) the operators are applied to propositional formulas, while iterations of probability operators are not allowed. Possible world semantics with a finitely additive probability measure on sets of worlds definable by formulas is defined, so that formulas remain true or false. The corresponding axiomatization is provided. The axiom system is infinitary. It contains an infinitary rule with countable many premisses and one conclusion. The rule is related to the Archimedean property of real numbers. The logic \(LPP_2\) is not compact: there are unsatisfiable sets of formulas that are finitely satisfiable. Some of the consequences of non-compactness are described. Then, soundness and strong completeness of the logic is proved with respect to several classes of probability models. This is followed by a proof of decidability of PSAT, the satisfiability problem for \(LPP_2\), which is NP-complete. Finally, a heuristic approach to PSAT is presented. This Chapter covers some results from Ikodinović et al., Int J Approx Reason, (55):1830–1842, 2014, [3], Jovanović et al., Variable neighborhood search for the probabilistic satisfiability problem, 2007, [4], Kokkinis et al., Logic J. IGPL, (23):662–687, 2015, [5], Ognjanović, J. Logic Comput, (9):181–195, 1999, [6], Ognjanović et al., Theor Comput Sci, (247):191–212, 2000, [7], Ognjanović et al., A genetic algorithm for satisfiability problem in a probabilistic logic, 2001, [8],Ognjanović et al., A Genetic Algorithm for Probabilistic SAT Problem, 2004, [9], Ognjanović et al., A Hybrid Genetic and Variable Neighborhood Descent for Probabilistic SAT Problem, 2005, [10], Ognjanović et al., Zbornik Radova, Subseries Logic in Computer Science, 2009, [11], Rašković and Ognjanović, Some propositional probabilistic logics, 1996, [12], Rašković and Ognjanović, A first order probability logic, \(LP_Q\), 1999, [13], Stojanović et al., Appl Soft Comput, (31):339–347, 2015, [14].
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Notes
- 1.
\(\varphi \) is a syntactical consequence of T.
- 2.
In other words, the length of a proof is an at most countable successor ordinal.
- 3.
A set of formulas, a theory, which is finitely satisfiable, but not realized (satisfiable).
- 4.
Which in the case of \(LPP_2\) coincides with non-isolated types.
- 5.
Theorem 3.2.10 from [1]. Let C be an algebra of subsets of a set \(\varOmega \) and \(\mu (w)\) a positive bounded charge—a finitely additive measure—on C. Let F be an algebra on \(\varOmega \) containing C. Then there exists a positive bounded charge \({\overline{\mu (w)}}\) on F such that \({\overline{\mu (w)}}\) is an extension of \(\mu (w)\) from C to F and that the range of \({\overline{\mu (w)}}\) is a subset of the closure of the range of \(\mu (w)\) on C.
- 6.
Carathéodory theorem 1.3.10 Let \(\mu \) be a measure on the algebra H, and assume that \(\mu \) is \(\sigma \)-finite, i.e.:
-
if \(\mathscr {F}_i \in H\), for \(i \in \mathbb {N}\), and \(\bigcup _i \mathscr {F}_i \in H\), then
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\(\mu (\bigcup _i \mathscr {F}_i) = \lim _{i} \mu (\mathscr {F}_0 \cup \ldots \cup \mathscr {F}_i)\).
Then \(\mu \) has a unique extension to a measure on the minimal \(\sigma \)-algebra \(\overline{H}\) over H.
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- 7.
Statements about complexity of the satisfiability problem for weight formulas from [2]. |A| and \(\Vert A\Vert \) denote the length of A (the number of symbols required to write A), and the length of the longest coefficient appearing in A, when written in binary, respectively. The size of a rational number a / b, where a and b are relatively prime, is defined to be the sum of lengths of a and b, when written in binary.
Theorem 2.6 Suppose A is a weight formula that is satisfied in some measurable probability structure. Then A is satisfied in a structure \((S, H, \mu , v)\) with at most |A| states where every set of states is measurable, and where the probability assigned to each state is a rational number with size \(O(|A| \Vert A\Vert + |A| \log (|A|))\).
Lemma 2.7 If a system of r linear equalities and/or inequalities with integer coefficients each of length at most l has a nonnegative solution, then it has a nonnegative solution with at most r entries positive, and where the size of each member of the solution is \(O(rl + r \log (r))\).
Lemma 2.8 Let A be a weight formula. Let \(M = (S, H, \mu , v)\) and \(M_0 = (S, H, \mu , v')\) be probability structures with the same underlying probability space \((S, H, \mu )\). Assume that \(v(w,p) = v'(w,p)\) for every state w and every primitive proposition p that appears in A. Then \(M \models A\) iff \(M_0 \models A\).
Theorem 2.9 The problem of deciding whether a weight formula is satisfiable in a measurable probability structure is \({\mathrm {NP}}\)complete.
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Ognjanović, Z., Rašković, M., Marković, Z. (2016). \(\mathbf {LPP_2}\), a Propositional Probability Logic Without Iterations of Probability Operators. In: Probability Logics. Springer, Cham. https://doi.org/10.1007/978-3-319-47012-2_3
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