EXTENSIONS OF DYNAMIC PROGRAMMING FOR COMBINATORIAL OPTIMIZATION
- Speaker(s)
- Mikhail Moshkov
- Affiliation
- KAUST
- Date
- June 6, 2014, 3:45 p.m.
- Room
- room 5440
- Seminar
- Research Seminar of the Logic Group: Approximate reasoning in data mining
The aim of usual Dynamic
Programming (DP) is to find an optimal object from a finite set
of objects. We
consider extensions of DP which allow us (i) to describe the set
of optimal
objects, (ii) to count the number of these objects, (iii) to
make sequential
optimization relative to different criteria, (iv) to find the
set of Pareto
optimal points for two criteria, and (v) to describe
relationships between two
criteria. The areas of applications include discrete
optimization, fault
diagnosis, complexity of algorithms, machine learning, and
knowledge
representation.