CISC 455 Evolutionary Optimization and Learning
CISC 455 Evolutionary Optimization and Learning Units: 3.00
Building, applying and studying algorithms based on the Darwinian principles of natural evolution. A creative approach to AI able to create novel solutions. Genetic algorithms, evolution strategies, and genetic programming. Application to optimization and learning problems.
Learning Hours: 120 (36 Lecture, 84 Private Study)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 365 and STAT 263).
Offering Faculty: Faculty of Arts and Science
Concurrent Education Degree Requirements
...3.0, CISC 102 /3.0, CISC 203...454 /6.0, MUSC 455 /6.0, MAPP...