171 citations
- Heriot-Watt UniversityGB4 papers
- Max Planck Institute for Gravitational PhysicsDE4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Data61AU3 papers
- İzmir University of EconomicsTR3 papers
- Laboratoire d'Informatique, de Robotique et de Microélectronique de MontpellierFR3 papers
- UNSW SydneyAU3 papers
- Boston UniversityUS2 papers
- Cardiff UniversityGB2 papers
- Center for Astrophysics Harvard & SmithsonianUS2 papers
- Jagiellonian UniversityPL2 papers
- Lancaster UniversityGB2 papers
13 papers · 1 filter
On Improving Local Search for Unsatisfiability
David Pereira, Inês Lynce, Steven Prestwich
Stochastic local search (SLS) has been an active field of research in the last few years, with new techniques and procedures being developed at an astonishing rate. SLS has been tr…
Brownian motion in a ball in the presence of spherical obstacles
Julie O'Donovan
We study the problem of when a Brownian motion in the unit ball has a positive probability of avoiding a countable collection of spherical obstacles. We give a necessary and suffic…
Multiset Ordering Constraints
Alan M. Frisch, Ian Miguel, Zeynep Kiziltan +2
We identify a new and important global (or non-binary) constraint. This constraint ensures that the values taken by two vectors of variables, when viewed as multisets, are ordered.…
Reasoning about soft constraints and conditional preferences: complexity results and approximation techniques
Carmel Domshlak, Francesca Rossi, Kristen Brent Venable +1
Many real life optimization problems contain both hard and soft constraints, as well as qualitative conditional preferences. However, there is no single formalism to specify all th…
Stationary hyperboloidal slicings with evolved gauge conditions
Frank Ohme, Mark Hannam, Sascha Husa +1
We analyze stationary slicings of the Schwarzschild spacetime defined by members of the Bona-Masso family of slicing conditions. Our main focus is on the influence of a non-vanishi…
Stochastic Constraint Programming
Toby Walsh
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision…