AVÊÓƵ

School of Engineering and Informatics (for staff and students)

Artificial Life (819G5)

Artificial Life

Module 819G5

Module details for 2024/25.

15 credits

FHEQ Level 7 (Masters)

Module Outline

The aim of this module is to provide an introduction to the field of Artificial Life (ALife). This has a dual role: firstly, taking inspiration from biology for engineering and AI in particular; secondly, using computational tools for testing ideas in biology.

Topics include:
Evolutionary computation
ALife models of biological systems
Dynamical systems analysis of complex systems
Non-symbolic approaches to cognition
Artificial chemistries

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.

Library

No set text. Reading is provided each week (journal and conference articles)

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.

TypeTimingWeighting
Coursework100.00%
Coursework components. Weighted as shown below.
ProjectA1 Week 2 100.00%
Timing

Submission deadlines may vary for different types of assignment/groups of students.

Weighting

Coursework components (if listed) total 100% of the overall coursework weighting value.

TermMethodDurationWeek pattern
Autumn SemesterLaboratory2 hours00001010000
Autumn SemesterLecture2 hours11111111111
Autumn SemesterSeminar1 hour11110101111

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Dr Chris Johnson

Assess convenor
/profiles/246069

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School of Engineering and Informatics (for staff and students)

School Office:
School of Engineering and Informatics, AVÊÓƵ, Chichester 1 Room 002, Falmer, Brighton, BN1 9QJ
ei@sussex.ac.uk
T 01273 (67) 8195

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