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Found 6 papers, 2 papers with code
Domain-Independent Dynamic Programming
We experimentally compare our DIDP solvers with commercial MIP and CP solvers (solving MIP and CP models, respectively) on common benchmark instances of eleven combinatorial optimization problem classes.
PRP Rebooted: Advancing the State of the Art in FOND Planning
Fully Observable Non-Deterministic (FOND) planning is a variant of classical symbolic planning in which actions are nondeterministic, with an action's outcome known only upon execution.
Domain-Independent Dynamic Programming: Generic State Space Search for Combinatorial Optimization
For combinatorial optimization problems, model-based approaches such as mixed-integer programming (MIP) and constraint programming (CP) aim to decouple modeling and solving a problem: the 'holy grail' of declarative problem solving.
(Unconstrained) Beam Search is Sensitive to Large Search Discrepancies
We find that increasing the beam width leads to sequences that are disproportionately based on early and highly non-greedy decisions.
Comparing and Integrating Constraint Programming and Temporal Planning for Quantum Circuit Compilation
Our hybrid methods use solutions found by temporal planning to warm start CP, leveraging the ability of the former to find satisficing solutions to problems with a high degree of task optionality, an area that CP typically struggles with.
Scheduling a Dynamic Aircraft Repair Shop with Limited Repair Resources
To solve the problem, we view the dynamic repair shop as successive static repair scheduling sub-problems over shorter time periods.
