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1. Constraint Optimization over Semirings

   A. Pavan; Kuldeep S Meel; N. V. Vinodchandranl Arnab Bhattacharyya (February 2023, Proceedings of the AAAI Conference on Artificial Intelligence)

   Williams Brian; Chen Yiling; Neville Jennifer (Ed.)

   Interpretations of logical formulas over semirings (other than the Boolean semiring) have applications in various areas of computer science including logic, AI, databases, and security. Such interpretations provide richer information beyond the truth or falsity of a statement. Examples of such semirings include Viterbi semiring, min-max or access control semiring, tropical semiring, and fuzzy semiring. The present work investigates the complexity of constraint optimization problems over semirings. The generic optimization problem we study is the following: Given a propositional formula $$\varphi$$ over $$n$$ variable and a semiring $$(K,+,\cdot,0,1)$$, find the maximum value over all possible interpretations of $$\varphi$$ over $$K$$. This can be seen as a generalization of the well-known satisfiability problem (a propositional formula is satisfiable if and only if the maximum value over all interpretations/assignments over the Boolean semiring is 1). A related problem is to find an interpretation that achieves the maximum value. In this work, we first focus on these optimization problems over the Viterbi semiring, which we call \optrustval\ and \optrust. We first show that for general propositional formulas in negation normal form, \optrustval\ and {\optrust} are in $${\mathrm{FP}}^{\mathrm{NP}}$$. We then investigate {\optrust} when the input formula $$\varphi$$ is represented in the conjunctive normal form. For CNF formulae, we first derive an upper bound on the value of {\optrust} as a function of the number of maximum satisfiable clauses. In particular, we show that if $$r$$ is the maximum number of satisfiable clauses in a CNF formula with $$m$$ clauses, then its $$\optrust$$ value is at most $$1/4^{m-r}$$. Building on this we establish that {\optrust} for CNF formulae is hard for the complexity class $${\mathrm{FP}}^{\mathrm{NP}[\log]}$$. We also design polynomial-time approximation algorithms and establish an inapproximability for {\optrustval}. We establish similar complexity results for these optimization problems over other semirings including tropical, fuzzy, and access control semirings. 

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2. Semiring Provenance for Fixed-Point Logic

   https://doi.org/10.4230/LIPIcs.CSL.2021.17  

   Dannert, K; Graedel, E; Naaf, N; Tannen, V (January 2021, Conference on Computer Science Logic, CSL 2021,)

   null (Ed.)

   Semiring provenance is a successful approach, originating in database theory, to providing detailed information on how atomic facts combine to yield the result of a query. In particular, general provenance semirings of polynomials or formal power series provide precise descriptions of the evaluation strategies or “proof trees” for the query. By evaluating these descriptions in specific application semirings, one can extract practical information for instance about the confidence of a query or the cost of its evaluation. This paper develops semiring provenance for very general logical languages featuring the full interaction between negation and fixed-point inductions or, equivalently, arbitrary interleavings of least and greatest fixed points. This also opens the door to provenance analysis applications for modal μ-calculus and temporal logics, as well as for finite and infinite model-checking games. Interestingly, the common approach based on Kleene’s Fixed-Point Theorem for ω-continuous semirings is not sufficient for these general languages. We show that an adequate framework for the provenance analysis of full fixed-point logics is provided by semirings that are (1) fully continuous, and (2) absorptive. Full continuity guarantees that provenance values of least and greatest fixed-points are well-defined. Absorptive semirings provide a symmetry between least and greatest fixed-points and make sure that provenance values of greatest fixed points are informative. We identify semirings of generalized absorptive polynomials S∞[X] and prove universal properties that make them the most general appropriate semirings for our framework. These semirings have the further property of being (3) chain-positive, which is responsible for having truth-preserving interpretations that give non-zero values to all true formulae. We relate the provenance analysis of fixed-point formulae with provenance values of plays and strategies in the associated model-checking games. Specifically, we prove that the provenance value of a fixed point formula gives precise information on the evaluation strategies in these games. 

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3. Estimating the Density of States of Boolean Satisfiability Problems on Classical and Quantum Computing Platforms

   https://doi.org/10.1609/aaai.v34i02.5524  

   Sahai, Tuhin; Mishra, Anurag; Pasini, Jose Miguel; Jha, Susmit (June 2020, Proceedings of the AAAI Conference on Artificial Intelligence)

   Given a Boolean formula ϕ(x) in conjunctive normal form (CNF), the density of states counts the number of variable assignments that violate exactly e clauses, for all values of e. Thus, the density of states is a histogram of the number of unsatisfied clauses over all possible assignments. This computation generalizes both maximum-satisfiability (MAX-SAT) and model counting problems and not only provides insight into the entire solution space, but also yields a measure for the hardness of the problem instance. Consequently, in real-world scenarios, this problem is typically infeasible even when using state-of-the-art algorithms. While finding an exact answer to this problem is a computationally intensive task, we propose a novel approach for estimating density of states based on the concentration of measure inequalities. The methodology results in a quadratic unconstrained binary optimization (QUBO), which is particularly amenable to quantum annealing-based solutions. We present the overall approach and compare results from the D-Wave quantum annealer against the best-known classical algorithms such as the Hamze-de Freitas-Selby (HFS) algorithm and satisfiability modulo theory (SMT) solvers. 

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4. Polynomial Time Convergence of the Iterative Evaluation of Datalogo Programs

   https://doi.org/10.1145/3695839  

   Im, Sungjin; Moseley, Benjamin; Ngo, Hung Q; Pruhs, Kirk (November 2024, Proceedings of the ACM on Management of Data)

   Datalog^ois an extension of Datalog that allows for aggregation and recursion over an arbitrary commutative semiring. Like Datalog, Datalogo programs can be evaluated via the natural iterative algorithm until a fixed point is reached. However unlike Datalog, the natural iterative evaluation of some Datalogo programs over some semirings may not converge. It is known that the commutative semirings for which the iterative evaluation of Datalogo programs is guaranteed to converge are exactly those semirings that are stable. Previously, the best known upper bound on the number of iterations until convergence over p-stable semirings is ∑i=1 ^n (p+2)ⁱ= Θ(pⁿ) steps, where n is (essentially) the output size. We establish that, in fact, the natural iterative evaluation of a Datalogo program over a p-stable semiring converges within a polynomial number of iterations. In particular our upper bound is O(σ p n²( n²lg Λ + lg σ)) where σ is the number of elements in the semiring present in either the input databases or the Datalogo program, and λ is the maximum number of terms in any product in the Datalogo program. 

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5. Sometimes Hoarding is Harder than Cleaning: NP-hardness of Maximum Blocked-Clause Addition

   https://doi.org/10.29007/p5mc  

   Subercaseaux, Bernardo (May 2024, EasyChair)

   Adding blocked clauses to a CNF formula can substantially speed up SAT-solving, both in theory and practice. In theory, the addition of blocked clauses can exponentially reduce the length of the shortest refutation for a formula [17, 19]. In practice, it has been recently shown that the runtime of CDCL solvers decreases significantly for certain instance families when blocked clauses are added as a preprocessing step [10,22]. This fact is in contrast to, but not in contradiction with, prior results showing that Blocked- Clause Elimination (BCE) is sometimes an effective preprocessing step [14,15]. We suggest that the practical role of blocked clauses in SAT-solving might be richer than expected. Concretely, we propose a theoretical study of the complexity of Blocked-Clause Addition (BCA) as a preprocessing step for SAT-solving, and in particular, consider the problem of adding the maximum number of blocked clauses of a given arity k to an input formula F. While BCE is a confluent process, meaning that the order in which blocked clauses are eliminated is irrelevant, this is not the case for BCA: adding a blocked clause to a formula might unblock a different clause that was previously blocked. This order-sensitivity turns out to be a crucial obstacle for carrying out BCA efficiently as a preprocessing step. Our main result is that computing the maximum number of k-ary blocked clauses that can be added to an input formula F is NP-hard for every k ≥ 2. 

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