COM3524 Bioinspired Computing

Aims/Description: This module focuses on modern artificial intelligence (AI) techniques and their inspiration from biological systems. Examples include evolution, multicellular tissues, neural systems, the immune system and swarms, inspiring abstractions such as evolutionary or swarm-based optimization algorithms, neural computing, as well computational approaches to simulate real world systems, (e.g. cellular automata and agent-based models). Lectures introduce a range of AI and related approaches in the context of their relevant biological inspiration and also their potential application to real word problems. A selection of optimisation and simulation techniques are explored in more depth using Python via active learning in computer laboratories. There is an emphasis on applying the scientific approach to practical work within this module.

Restrictions on availability: Available to students in Computer Science only. Students must have existing coding skills in Python.

Staff Contact: WALKER DAWN C

Teaching Methods: Lectures, Laboratory work, Independent Study

Assessment: Formal Exam, Project/ portfolio

Information on the department responsible for this unit (Computer Science):

Departmental Home Page

Teaching timetable

NOTE The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

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Teaching methods and assessment displayed on this page are indicative for 2025-26.