🧬 COMP5400 Coursework 2 Project Plan

Topic: Simulating Neural System Evolution in Simple Organisms Using Conway’s Game of Life
Team: Hemant and Angie
Report Due: 6 May
Presentation: 12 May

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🗓️ Phase 1: Project Setup & Initial Research

Timeline: 18 - 20 March

Hemant

• Finalize organism choice (C. elegans)
• Set up GitHub repository
• Review Evolutionary Algorithms (Evolution-1, Evolution-2)
• Summarize key points from genetic algorithms & evolution lectures (Coevolution-1, Coevolution2)

Angie

• Review Neural Network literature (Hebbian & Hopfield Networks)
  (Hebbian-Learning, COMP5400M 10 Hopfield)
• Summarize key module references (neural spiking & excitability)
  (COMP5400M Lecture 9)

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🗓️ Phase 2: Basic Implementation of Conway’s Game of Life

Timeline: 21 - 24 March

Hemant

• Python setup & basic implementation of Conway’s GoL
• Initial documentation explaining implementation clearly in README

Angie

• Visualization (matplotlib or pygame)
• Document rules, logic, pseudocode clearly

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🗓️ Phase 3: Neural Network & Genetic Algorithm Framework

Timeline: 25 - 28 March

Hemant

• Implement Genetic Algorithm framework:
  • Define clear fitness function
  • Implement selection, mutation, crossover mechanisms
• Documentation of genetic algorithm (README.md, inline comments)

Angie

• Define & implement simplified neural architecture (inspired by Hopfield networks)
• Integrate neural architecture with genetic algorithm
• Document neural network implementation clearly (inline comments, README.md)

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🟢 Pause Project Clearly Documented (29 March - 21 April)
Holiday pause for Maths Module Revision

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🗓️ Phase 4: Advanced Features & Testing

Timeline: 22 - 27 April

Hemant

• Fine-tune genetic algorithm parameters
• Conduct extensive testing & debugging of the overall simulation
• Document parameter tuning decisions

Angie

• Implement Hebbian Learning dynamics (optional, advanced)
• Generate clear result visualizations (fitness plots, neural evolution snapshots)
• Document visualization outcomes

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🗓️ Phase 5: Report Writing & Documentation

Timeline: 28 April - 4 May
Due: 6 May

Hemant

• Write Report Sections:
  • Introduction & motivation clearly defined
  • Methodology (GA, GoL)
  • Discussion & conclusions
• Finalize README.md clearly for code submission

Angie

• Write Report Sections:
  • Literature review clearly referenced
    (Evolution-1, Hebbian-Learning, Evolution-2, COMP5400M 10 Hopfield)
  • Methodology (Neural architecture)
  • Results & visualizations
• Proofread and edit entire final report

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🗓️ Phase 6: Presentation Preparation & Practice

Timeline: 5 - 11 May
Presentation: 12 May (8 mins + Q&A)

Hemant

• Create slides for:
  • Project introduction & motivation
  • Methodology (GA & GoL)
  • Summary of conclusions & insights
• Practice presentation clearly & time it within 8 minutes

Angie

• Create slides for:
  • Background (clearly referencing module material)
    (COMP5400M Lecture 9, Hebbian-Learning, COMP5400M 10 Hopfield)
  • Neural network architecture clearly explained
  • Results & visualizations
• Moderate Q&A practice session
• Practice presentation clearly & time it within 8 minutes

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📌 Key Checkpoints & Deliverables

Checkpoint	Deadline	Responsible
Project Setup & Literature	20 March	Hemant & Angie
GoL Implementation Done	24 March	Hemant & Angie
Neural Evolution Functional	28 March	Hemant & Angie
Holiday Pause (Clear Documentation)	29 March	Hemant & Angie
Resume & Advanced Features	27 April	Hemant & Angie
Draft Report Completion	4 May	Hemant & Angie
🚩 Report Submission	6 May	Hemant
🚩 Final Presentation	12 May	Hemant & Angie

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🛠️ Tools & Communication

• Code Management: GitHub
• Documentation: Google Docs, Markdown
• Communication: Discord or Slack
• Check-ins: Daily text status, bi-weekly detailed discussions

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📚 Module Integration (Clearly include these references in report & presentation)

• Evolutionary Algorithms & Co-Evolution
  (Coevolution-1, Coevolution2, Evolution-1, Evolution-2)

• Neural Networks & Hebbian Learning
  (Hebbian-Learning, COMP5400M 10 Hopfield)

• Artificial Life & Cellular Automata
  (lec1-2025)

• Swarm Intelligence & Collective Behaviour
  (swarm_intelligence_2, swarm_intelligence_1)