Search Results for author:
Found 3 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.
Learning Search-Space Specific Heuristics Using Neural Networks
We propose and evaluate a system which learns a neuralnetwork heuristic function for forward search-based, satisficing classical planning.
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.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
