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Biologically Inspired Computing F21BC2:  2015/16

General Notes on Course Delivery 

Note:    The lecture slides and other materials that are scheduled later than today’s date are not necessarily complete and/or correct.  

DC (David Corne) Lectures are green     PV (Patricia Vargas) lectures are blue    ML (Michael Lones) lectures are yellow

A White lecture slot means that no class is planned – however sometimes these slots may be used, for example to replace lectures that had to be cancelled. In those cases, we will of course let you know as far as possible in advance.

DC Office hour   Thursdays 4:15—5:15   

PV Office hour: Tuesdays 2:15---3:15 (To be confirmed)

ML Office hour:  Wednesday 10:15—11:15


The SCHEDULE below is correct, but the ‘FUTURE’ Lecture and Coursework material is always subject to change

Week beginning

Tuesday 16:15  in EM 3.06

Thursday 15:15  in EM 3.06

Coursework out

Coursework in

Mandatory additional material

Recommended reading

Mon 14th Sep

DC   Overview of module and intro to Bio-Inspired Computing - ppt

DC Evolutionary Computation ppt

 DC hands out coursework 1 (10% of module)  

CW1 (ppt)


Hard and Easy optimization problems

Study the upcoming   encodings lecture to help with CW1

simple interactive evolution

simple EA/TSP demo (not quite finished)

Mon 21st  Sep

PV Introduction to Neurocomputation (pdf)

 PV Artificial Neural Networks I  (pdf)



Neural computation tutorial questions and bibliography

Mon 28th Sep

DC  EAs: Details, Encodings, Operators and CW1 ppt

PV Artificial Neural Networks II (pdf)


  coursework  1.1

Deadline 23:59pm Sun 4th Oct

more encodings ppt  

Selection ppt  

Operators  ppt  

Freitas paper   pdf

Falkenauer paper   pdf


Mon 5th Oct

PV Artificial Neural Networks IV (pdf)

DC  Hillclimbing, Landscapes, Neighbourhoods, Local Search ppt



Operators ( as above)  ppt – describing line/box crossover  & Gaussian mut

Here is the SNNS ANN simulator

and some further info from Patricia

Selected EA Applications paper  pdf 

Mon 12th Oct

DC  Indirect encodings and hyper-heuristics ppt



Reynolds’ paper  



A nice explanation of Reynolds’ rules 

DC’s PSO app  (currently broken)

Swarm Intelligence chapter pdf

Mon 19th  Oct

PV Artificial Neural Networks V (pdf)

PV GasNets lecture (pdf)

Renan Moioli’s invited GasNets lecture  pdf

PV hands out coursework 2 (20% of module)  

 CW2 pdf

CW2 Data (zip)

coursework  1.2

Deadline 23:59pm Sun 25th Oct



Mon 26th Oct

DC  Swarm Intelligence     ppt  

DC  Ant Colony Optimization    ppt







Mon 2nd   Nov

ML Foundations of Genetic Programming pdf

ML  GP: Memory and loops pdf

 ML hands out coursework 3 (ON VISION) (20% of module)

cw3 pdf

zip of ecj




Mon 9th  Nov

ML GP: Language and Representation  pdf

ML:  Cellular automata  pdf



Handin coursework  2


HANDIN to School Office by

3pm 16th November

DC’s CA / forest fire app

DC’s 1dca app

CA urbanization paper  CA traffic simulation paper  CA flu paper  CA brain tumour paper  CA and P Systems for HIV

Mon 16th  Nov

ML Gene regulatory models pdf

ML: Evolvable hardware (possibly guest lecture)





Mon 23rd   Nov

ML Artifical biochemical networks  pdf

DC  Particle Swarm Optimization   ppt




Mon 30th    Nov


Slot to be used if necessary

DC revision lecture


  Handin Coursework 3

Deadline 3pm Friday 4th December at School Office




DC = David Corne, who will generally lecture about bio-inspired methods for optimisation, with a focus on evolutionary computation (aka genetic algorithms) – broadly this is about how certain aspects of nature (evolution, swarm behaviour) lead to very effective optimisation and design methods.

PV = Patricia Vargas, who will generally lecture about neural computation, and some popular and effective combinations of neural and evolutionary computation, including evolutionary robotics.  

Coursework Handin :  CW1 handin in all cases should be by email with the coursework as a ppt or pdf attachment, emailled to DWC at, subject line either: “BIC CW1 Slide X” . Include your name in the pdf!

Feel completely free to email any of us at any time about any query regarding the lecture material – you will appreciate that you may rarely get an immediate reply, but we will try to get back to you as soon as possible, and arrange meetings to discuss issues where necessary.


50% coursework and 50% exam.

CW 1 (DC): 10%    CW2 (pv): 20%    CW3 (ML): 20%

As in previous years, the exam will have 4 questions, and you are required to answer only 3 questions for full marks.

Here are some Past papers:  2012,   2013,   2014   . Note that: we used to teach ‘DNA computing’ on this module, but we don’t teach that now. Obviously, you will therefore not get questions like  Q1(b) or Q4 in the 2012 paper .  Also, this year is the first time that Michael Lones has been involved; so, your paper may or may not involve questions based on the ML lectures.

Here are some notes about the exam, and about revising for DWC’s part of the course:  pdf