1 citations · 1 across the 6 of their papers we have counts for
11 papers
Automatic Feature Learning for Essence: a Case Study on Car Sequencing
Alessio Pellegrino, Özgür Akgün, Nguyen Dang +2
Constraint modelling languages such as Essence offer a means to describe combinatorial problems at a high-level, i.e., without committing to detailed modelling decisions for a part…
Towards Reformulating Essence Specifications for Robustness
Özgür Akgün, Alan M. Frisch, Ian P. Gent +4
The Essence language allows a user to specify a constraint problem at a level of abstraction above that at which constraint modelling decisions are made. Essence specifications are…
Efficient Incremental Modelling and Solving
Gökberk Koçak, Özgür Akgün, Nguyen Dang +1
In various scenarios, a single phase of modelling and solving is either not sufficient or not feasible to solve the problem at hand. A standard approach to solving AI planning prob…
Exploring Instance Generation for Automated Planning
Özgür Akgün, Nguyen Dang, Joan Espasa +3
Many of the core disciplines of artificial intelligence have sets of standard benchmark problems well known and widely used by the community when developing new algorithms. Constra…
Towards Portfolios of Streamlined Constraint Models: A Case Study with the Balanced Academic Curriculum Problem
Patrick Spracklen, Nguyen Dang, Özgür Akgün +1
Augmenting a base constraint model with additional constraints can strengthen the inferences made by a solver and therefore reduce search effort. We focus on the automatic addition…
Conjure Documentation, Release 2.3.0
Özgür Akgün, András Salamon
Conjure is an automated modelling tool for Constraint Programming. In this documentation, you will find the following: A brief introduction to Conjure, installation instructions, a…