Reference number : GC-2017-Q1-03009, amendment number : , agreement type : G, recipient legal name : Ternovska, Evgenia (Simon Fraser University), recipient country : CA, recipient province : nan, recipient city : British Columbia|Colombie-Britannique, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : I propose to develop theoretical foundations for representing complex modular systems, a high-level programming language to specify such systems, and algorithms for finding solutions. The research will help businesses and other organizations to deal with an increasing amount of information and with increasingly complex tasks (including combinatorial optimization). Because of the complexity of the problem, the proposed research will proceed in three directions: 
1) Develop a scalable knowledge representation formalism that supports modular high-level (declarative) problem solving; 
2) Develop a computational framework with parameters to control its expressive power and the computational complexity of finding solutions; 
3) Develop algorithmic techniques for solving and synthesizing modular systems. 
The scientific progress will be measured both in theoretical results and in the development and thorough evaluation of prototype systems. One of the core deliverables will be an adaptation of the technological ideas by a potential industrial partner. 
The proposed research has potential to contribute to the theory of computing, through developing new techniques for complexity analysis, and to technology, by offering a language with associated tools, that allows one to combine different solvers and (potentially only partially visible) databases for solving problems of a new magnitude., program purpose french : I propose to develop theoretical foundations for representing complex modular systems, a high-level programming language to specify such systems, and algorithms for finding solutions. The research will help businesses and other organizations to deal with an increasing amount of information and with increasingly complex tasks (including combinatorial optimization). Because of the complexity of the problem, the proposed research will proceed in three directions: 
1) Develop a scalable knowledge representation formalism that supports modular high-level (declarative) problem solving; 
2) Develop a computational framework with parameters to control its expressive power and the computational complexity of finding solutions; 
3) Develop algorithmic techniques for solving and synthesizing modular systems. 
The scientific progress will be measured both in theoretical results and in the development and thorough evaluation of prototype systems. One of the core deliverables will be an adaptation of the technological ideas by a potential industrial partner. 
The proposed research has potential to contribute to the theory of computing, through developing new techniques for complexity analysis, and to technology, by offering a language with associated tools, that allows one to combine different solvers and (potentially only partially visible) databases for solving problems of a new magnitude., agreement title english : Scalable Knowledge Representation and Solving, agreement title french : Scalable Knowledge Representation and Solving, agreement number : RGPIN, agreement value : 115000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada