Computing

Artificial Life

Module code: 819G5
Level 7 (Masters)
15 credits in autumn teaching
Teaching method: Laboratory, Lecture, Seminar
Assessment modes: Coursework

This module provides you with an introduction to the new field of artificial life. The module has a dual focus: first in bringing computing ideas from biology to AI that are useful in synthesising hardware and software-lifeline artefacts, and secondly using computational tools for testing ideas in biology.

Topics that you will study include: cellular automata and random Boolean networks; models of growth and development; introduction to evolutionary algorithms; dynamical system approaches to cognition; coevolution; fitness landscapes; and information theory and life.

Pre-requisite

The module assumes an ability to write software in one appropriate programming language (e.g. Java, C, Python, Matlab). Basic knowledge of formal computational skills is also assumed.

Module learning outcomes

  • Demonstrate critical awareness of current issues in Artificial Life research.
  • Programme and apply a genetic algorithm.
  • Use dynamical systems techniques to analyse a complex system.
  • Design, complete and critically assess a small but original artificial life research project.