Nature Inspired Computation

Objectives

  • Discuss ways of representing solutions for the application of naturally inspired algorithms
  • Develop evolutionary algorithms
  • Design socially inspired algorithms
  • Identify convergence problems
  • Discuss mechanisms for increasing diversity
  • Develop algorithms with different population structures
  • Design multi-objective optimisation algorithms
  • Rigorously evaluate various approaches to problems using statistics

Program

  • Solution coding
  • Evolution-inspired algorithms
  • Socially Inspired Algorithms
  • Convergence and Diversity
  • Population Structures
  • Multi-Objective Optimisation
  • Statistical Analysis of Results)

Bibliography

  • Introduction to Evolutionary Computation (2nd edition), A. Eiben and J. Smith, Springer, 2015.
  • Bio-Inspired Artificial Intelligence: theories, methods, and Technologies, Dario Floreano and Claudio Mattiussi, MIT Press, 2008
  • Fundamentals of Natural Computing: basic concepts, algorithms, and applications, Leandro Castro, Chapman and Hall, 2006
  • Essentials of metaheuristics, Sean Luke, Lulu Press, 2009.
  • Clever algorithms: nature-inspired programming Recipes, Jason Brownlee, ISBN 978-1-4467-8506-5, 2011)

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