Cadoli, M., Giovanardi, A., Schaerf, M.: An Algorithm to Evaluate Quantified Boolean Formulae. In: Proc. of the 15th Nat. Conf. on Artificial Intelligence. (1998) 262--267 Home/Search Document Details and Download
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I N F S Y S R E S E a R C H - Institut Ur Informationssysteme (Correct)
....are harder than , and thus not polynomially reducible to SAT testing. Moreover, these problems cannot be reduced to any solver for problems that are located in the Polynomial Hierarchy. On the other hand, they are solvable in polynomial space, and thus reducible to a QBF solver (e.g. [4, 32, 8]) in polynomial time. Furthermore, testing probabilistic causal irrelevance is easier than C complete problems, which could perhaps help in finding polynomial time (randomized) approximation algorithms for this problem. We remark that for computing the conditional probability over two causal ....
M. Cadoli, A. Giovanardi, and M. Schaerf. An algorithm to evaluate quantified boolean formulae. In Proceedings AAAI-98, pages 262--267, 1998.
Complexity Results for Explanations in the Structural-Model.. - Eiter, Lukasiewicz (2002) (Correct)
....be utilized for this purpose, or the diagnostic frontend of the DLV system [10] Another possibility would be an encoding of causal explanations in Answer Set Programming, and using the DLV engine to compute solutions. For the case of general causal explanations, reductions to QBF solvers such as [5, 41, 19] could be used. 7.2 Bayesian Networks After Cooper s well known intractability result [7] for probabilistic inference in Bayesian networks, a number of papers in this area have investigated complexity issues for reasoning and in particular for explanation finding. A dominating notion of ....
M. Cadoli, M. Schaerf, A. Giovanardi, and M. Giovanardi. An algorithm to evaluate quantified boolean formulae and its experimental evaluation. Journal of Automated Reasoning, 28:101--142, 2002.
Algorithms for Logic-Based Abduction - Anja Remshagen And (Correct)
.... are maximum among all such assignments. Q ALL SAT is a special form of a quantified Boolean formula which contains two subformulas in conjunctive normal form (CNF) First solution algorithms for quantified Boolean formulas have been constructed, for example, by Cadoli, Giovanardi, and Schaerf [2] and Rintanen [7] These algorithms consider the case where all quantifiers constitute a prefix of a CNF formula. They cannot be applied to logic based abduction. We will propose algorithms for Q ALL SAT and its related problems that can take advantage of any efficient SAT solver and of any solver ....
Cadoli, M., Giovanardi, A., Schaerf, M.: An Algorithm to Evaluate Quantified Boolean Formulae. Proceedings of the Fifteenth National Conference on Artificial Intelligence (1998)
Optimizing a BDD-based Modal Solver - Pan, Vardi (Correct)
....and QBF have PSPACE complete decision problems [16, 31] This implies that the two problems are polynomially reducible to each other. A natural reduction from QBF to K is described in [12] In the last few years extensive effort was carried out into the development of highly optimized QBF solvers [17, 5]. One motivation for this effort is the hope of using QBF solvers as generic search engines [25] much in the same way that SAT solvers are being used as generic search engines. This suggests that another approach to K satisfiability is to find a natural reduction of K to QBF, and then apply a ....
....much in the same way that SAT solvers are being used as generic search engines. This suggests that another approach to K satisfiability is to find a natural reduction of K to QBF, and then apply a highly optimized QBF solver. We describe now such a reduction. A similar approach is suggested in [5] without providing either details or results. QBF is an extension of propositional logic with quantifiers. The set of QBF formulas is constructed from a set = fx 1 ; xn g of Boolean variables, and closed under the Boolean connectives and : as well as the quantifier 8x i . As usual, we ....
M. Cadoli, M. Schaerf, A. Giovanardi, and M. Giovanardi. An algorithm to evaluate quantified Boolean formulae and its experimental evaluation. Technical report, Dipartmento di Imformatica e Sistemistica, Universita de Roma, 1999.
On Computing Solutions to Belief Change Scenarios - Delgrande, al. (2003) (Correct)
....[34; 39] The general mechanism of our approach is to translate (in polynomial time) a given reasoning task into the evaluation problem for QBFs and then use a QBF evaluator to compute the resultant instances. The existence of efficient QBF solvers, such as the systems developed by Cadoli et al. [4] , Giunchiglia et al. 18] Rintanen [32] or Feldmann et al. 15] makes such a rapid prototyping approach practicably applicable. A similar approach for solving various reasoning tasks belonging to the area of nonmonotonic reasoning has been realized in the system QUIP [12; 11; 27] This ....
M. Cadoli, A. Giovanardi, and M. Schaerf. An Algorithm to Evaluate Quantified Boolean Formulae. In Proceedings of the AAAI National Conference on Artificial Intelligence, pages 262--267, Madison, Wisconsin, 1998.
Default Reasoning from Conditional Knowledge Bases.. - Eiter, Lukasiewicz (2000) (2 citations) (Correct)
....theorem provers for logics with complexity up to 2 are needed as host for efficient translations. For example, DLV [78] DeRes [23] or a disjunctive extension of smodels [75] which all provide this expressiveness, might be used, as well as theorem provers based on quantified Boolean formulas [20, 83, 32]. However, efficient transformations of the problems to these logics remain to be designed. In the case of problems with complexity P , such translations might not be very appealing, since the theorem provers mentioned above are tailored for solving problems whose complexity characteristics ....
M. Cadoli, A. Giovanardi, and M. Schaerf. An algorithm to evaluate quantified Boolean formulae. In Proc. 16th National Conference on AI (AAAI-98), Madison, WI, pp. 262--267, AAAI Press/MIT Press, 1998.
Modal Nonmonotonic Logics Revisited: Efficient.. - Eiter, Klotz.. (2002) (Correct)
....based on a reduction approach. The central idea is to translate a given reasoning task into a quantified Boolean formula (QBF) and then applying some sophisticated QBF solver to evaluate the translated QBF. The existence of efficient QBF solvers, like, e.g. the systems developed by Cadoli et al. [5], Giunchiglia et al. 18] Rintanen [37] Letz [25] or Feldmann et al. 15] makes this reduction approach practicably applicable. Concerning the particular reductions, we provide efficient (polynomial time) translations of reasoning tasks for the following modal nonmonotonic logics: Moore s ....
....by the availability of several practicably efficient QBF solvers. Among the different tools, there is a propositional theorem prover, boole, based on binary decision diagrams, a system using a generalised resolution principle [23] several provers implementing an extended Davis Putnam procedure [5, 15, 18, 25, 37], as well as a distributed algorithm running on a PC cluster [15] With the exception of boole, these tools do not accept arbitrary QBFs, but require the input formula to be in prenex conjunctive normal form. To avoid an exponential increase of formula size, structure preserving normal form ....
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M. Cadoli, A. Giovanardi, and M. Schaerf. An Algorithm to Evaluate Quantified Boolean Formulae. In Proc. AAAI-98, pages 262--267, 1998.
Complexity of Nested Circumscription and Nested.. - Cardoli, Eiter, Gottlob (2002) Self-citation (Cadoli) (Correct)
....related KR formalism or logic, or by designing genuine algorithms. Su s CS program [49] and Doherty et al. s DLS algorithm [16, 28] which handle the case of predicate logic, are incomplete in general and presumably not highly efficient in the propositional context. The use of QBF solvers (e.g. [11, 44, 23]) is here a suggestive starting point for obtaining more suitable systems. As we believe, addressing these issues is worthwhile since nesting circumscriptions is a natural generalization of circumscription, and yields, as shown by our results, a simple yet expressive knowledge representation ....
M. Cadoli, M. Schaerf, A. Giovanardi, and M. Giovanardi. An algorithm to evaluate quantified Boolean formulae and its experimental evaluation. Journal of Automated Reasoning, 28:101--142, 2002.
Fault Tolerance Analysis of Distributed.. - Feldmann, Haubelt.. (2003) (Correct)
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Cadoli, M., Giovanardi, A., Schaerf, M.: An Algorithm to Evaluate Quantified Boolean Formulae. In: Proc. of the 15th Nat. Conf. on Artificial Intelligence. (1998) 262--267
Finding Small Unsatisfiable Cores to Prove.. - Interian, Corvera.. (Correct)
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M. Cadoli, A. Giovanardi, and M. Schaerf. An algorithm to evaluate quantified boolean formulae. In AAAI '98/IAAI '98: Proceedings of the fifteenth national/tenth conference on Artificial 11 intelligence/Innovative applications of artificial intelligence, pages 262--267. American Association for Artificial Intelligence, 1998.
On Computing Belief Change Operations Using Quantified.. - Delgrande, Schaub, al. (Correct)
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M. Cadoli, A. Giovanardi, and M. Schaerf. An algorithm to evaluate quantified Boolean formulae. In Proceedings of the 15th National Conference on Artificial Intelligence (AAAI '98), pages 262--267, Madison, Wisconsin, 1998.
Encoding Connect-4 Using Quantified Boolean Formulae - Gent, Rowley (2003) (Correct)
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Cadoli, M., Giovanardi, A., Schaerf, M.: An algorithm to evaluate quantified Boolean formulae. In: AAAI-98. (1998) 262--267 http://www.dis.uniroma1.it/pub/AI/papers/cado-giov-scha-98.ps.gz.
Encoding Quantified CSPs as Quantified Boolean Formulae - Gent, Nightingale, Rowley (2004) (Correct)
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M. Cadoli, M. Schaerf, A. Giovanardi, and M. Giovanardi, `An algorithm to evaluate quantified boolean formulae and its experimental evaluation ', Journal of Automated Reasoning, 28(2), 101--142, (2002).
Solution Learning and Solution Directed Backjumping, Revisited - Gent, Rowley (2004) (Correct)
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M. Cadoli, M. Schaerf, A. Giovanardi, and M. Giovanardi, `An algorithm to evaluate quantified boolean formulae and its experimental evaluation', Journal of Automated Reasoning, 28(2), 101--142, (2002).
A Polynomial Translation of Logic Programs with.. - Pearce, Sarsakov, .. (2002) (6 citations) (Correct)
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M. Cadoli, A. Giovanardi, and M. Schaerf. An Algorithm to Evaluate Quantified Boolean Formulae. In Proc. AAAI-98, pages 262--267, 1998.
A Constraint-Propagation Approach to Quantified Constraints - Bordeaux (Correct)
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M. Cadoli, A Giovanardi, and M. Schaerf. An algorithm to evaluate quantified boolean formulae. In Proc. of the 15th Nat. Conf. on Artificial Intelligence (AAAI), pages 262--267, Madison, USA, 1999. AAAI/MIT Press. See also extended version (Tech Report DIS 08-99).
Using Stochastic Local Search to Solve Quantified Boolean.. - Gent, Hoos, Rowley, Smyth (2003) (1 citation) (Correct)
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Cadoli, M., Giovanardi, A., Schaerf, M.: An algorithm to evaluate quantified Boolean formulae. In: AAAI-98. (1998) 262--267
Algorithms for Quantified Constraint Satisfaction Problems - Nikos Mamoulis Department (2004) (1 citation) (Correct)
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Cadoli, M.; Giovanardi, A.; and Schaerf, M. 1998. An algorithm to evaluate quantified boolean formulae. In Proceedings of AAAI-98, 262--267.
Using Stochastic Local Search to Solve Quantified - Boolean Formulae Ian (2003) (1 citation) (Correct)
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Cadoli, M., Giovanardi, A., Schaerf, M.: An algorithm to evaluate quantified Boolean formulae. In: AAAI-98. (1998) 262--267
An Analysis of Empirical Testing for Modal Decision.. - Horrocks.. (2000) (22 citations) (Correct)
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M. Cadoli, A. Giovanardi, and M. Schaerf. An algorithm to evaluate quantified Boolean formulae. In Proceedings of the 15th National Conference on Artificial Intelligence (AAAI-98), pages 262--267. AAAI Press, 1998.
Watching Clauses in Quantified Boolean Formulae - Andrew Rowley University (2003) (Correct)
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Cadoli, M., Schaerf, M., Giovanardi, A., Giovanardi, M.: An algorithm to evaluate quantified boolean formulae and its experimental evaluation. Journal of Automated Reasoning 28 (2002) 101--142
Paraconsistent Reasoning via Quantified Boolean.. - Besnard, Schaub.. (Correct)
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M. Cadoli, A. Giovanardi, and M. Schaerf. An Algorithm to Evaluate Quantified Boolean Formulae. In Proc. AAAI-98, pages 262--267. AAAI Press, 1998.
Using Stochastic Local Search to Solve Quantified Boolean.. - Gent, Hoos, Rowley, Smyth (2003) (1 citation) (Correct)
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M. Cadoli, A. Giovanardi, and M. Schaerf. An algorithm to evaluate quantified Boolean formulae. In AAAI-98, pages 262--267, 1998.
Algorithms and Experiments on Finding Minimal - Models Paolo Liberatore (Correct)
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M. Cadoli, A. Giovanardi, and M. Schaerf. An algorithm to evaluate quantified boolean formulae. In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), pages 263--267, 1998.
On Deciding Subsumption Problems - Egly, Pichler, Woltran (2003) (1 citation) (Correct)
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Cadoli, M., A. Giovanardi, and M. Schaerf: 1998, `An Algorithm to Evaluate Quantified Boolean Formulae'. In: Proceedings of the 15th National Conference on Artificial Intelligence (AAAI'98). pp. 262--267.
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