Titlebook: Integration of Constraint Programming, Artificial Intelligence, and Operations Research; 21st International C Bistra Dilkina Conference pro

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Bi-objective Discrete Graphical Model Optimization,e, we introduce a dedicated higher-order constraint, which bounds the value of one GM-defined objective while minimizing another GM on the same variables. Discrete GM optimization is NP-hard, and its bi-objective variants are even harder. We show how existing GM global lower and upper bounds can be

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,An Exploration of Exact Methods for Effective Network Failure Detection and Diagnosis,nt integer linear programming (ILP), constraint programming (CP) and Maximum Satisfiability (MaxSAT) formulations for these problems and compare their performance. Using 625 network topologies, we demonstrate that employing such exact methods can reduce the number of monitors needed compared to the

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,UNSAT Solver Synthesis via Monte Carlo Forest Search,bution of unsatisfiable problem instances. Knuth Synthesis is the first RL approach to avoid the prohibitive costs of policy evaluations in an exponentially-sized tree, leveraging two key ideas: first, we estimate tree size by randomly sampling paths and measuring their lengths, drawing on an unbias

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