Module 06-35376 (2022)
Evolutionary Computation (Extended)
Level 4/M
Shan He | Semester 2 | 20 credits |
Outline
Evolutionary algorithms (EAs) are a class of optimisation techniques drawing inspiration from principles of biological evolution. They typically involve a population of candidate solutions from which the better solutions are selected, recombined, and mutated to form a new population of candidate solutions. This continues until an acceptable solution is found. Evolutionary algorithms are popular in applications where no problem-specific method is available, or when gradient-based methods fail. They are suitable for a wide range of challenging problem domains, including dynamic and noisy optimisation problems, constrained optimisation problems, and multi-objective optimisation problems. EAs are used in a wide range of disciplines, including optimisation, engineering design, machine learning, financial technology (“fintech”), and artificial life. In this module, we will study the fundamental principles of evolutionary computation, a range of different EAs and their applications, and a selection of advanced topics which may include time-complexity analysis, neuro-evolution, co-evolution, model-based EAs, and modern multi-objective EAs. The students will also read selected recent research articles on evolutionary computation.
Learning Outcomes
On successful completion of this module, the student should be able to:
- Describe, and apply the principles of evolutionary computation
- Explain and compare different evolutionary algorithms
- Design and adapt evolutionary algorithms for non-trivial problems
- Demonstrate an awareness of the current literature in this area
Pre-requisites
- 06-30175 - Data Structures & Algorithms
- 06-35324 - Mathematical and Logical Foundations of Computer Science
- 06-34238 - Artificial Intelligence 1
- 06-34255 - Artificial Intelligence 2
Cannot be taken with
- 06-35310 - Evolutionary Computation
Assessment
- Main Assessments: Continuous assessment (50%) and an examination (50%)
- Supplementary Assessments: Examination (100%)
Programmes containing this module
- MEng Computer Science/Software Engineering [4754]
- MEng Computer Science/Software Engineering with an Industrial Year [9501]
- MRes Natural Computation [9048]
- MSc Artificial Intelligence and Machine Learning [475D]
- MSc Robotics [9889]
- MSci Computer Science [4443]
- MSci Computer Science with an Industrial Year [9509]
- MSci Computer Science with Study Abroad [5576]
- MSci Mathematics and Computer Science [5197]
- MSci Mathematics and Computer Science with an Industrial Year [9496]