Jo Devriendt
Supervisor: Marc Denecker
January 5th 2017
Pick a satisfying solution from a set of candidate solutions
Automated systems
In:
- description of candidate solutions (simple)
- description of satisfying solutions (complex)
Out:
- satisfying solution
Abstraction in thesis:
model expansion problem
in predicate and propositional logic
In:
- vocabulary + domain
- theory + input structure
Out:
- model to theory
Pick a satisfying solution from a set of candidate solutions
Permutation on the set of candidate solutions
preserving satisfaction
Partitions candidate solutions into symmetry classes
Potential exponential blow-up of search space.
This blow-up is a fundamental problem of current combinatorial search technology and must be addressed.
Performs well on Pigeonhole :)
(Kodkod, Paradox)
(Sbass)
Satisfying solutions have an associated objective function.
Move locally through solution space optimizing the objective function.
Existing work
Existing work
Symmetrical Learning Scheme: learn symmetrical variants of learned clause
Good idea, but what symmetrical variants to learn?
Our work
Weakly inactive symmetries also lead to useful symmetrical propagations!
Our work
Simple and elegant.
New symmetry breaking preprocessor for SAT and ground ASP
Useful predicate level notion of symmetry
Automated local search through symmetry
Efficient variant of symmetric learning