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Evolutionary Algorithms Simon M. Lucas. The basic idea Initialise a random population of individuals repeat { evaluate select vary (e.g. mutate or crossover)

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Presentation on theme: "Evolutionary Algorithms Simon M. Lucas. The basic idea Initialise a random population of individuals repeat { evaluate select vary (e.g. mutate or crossover)"— Presentation transcript:

1 Evolutionary Algorithms Simon M. Lucas

2 The basic idea Initialise a random population of individuals repeat { evaluate select vary (e.g. mutate or crossover) } until satisfied, or timeup

3 Idea: fitness evolves over time

4 What to evolve? Parameter vectors for parametric solution Computational machines –E.g. Finite state machines –Neural networks –Computer programs Expression trees OO programs

5 Current Research Evolving game playing agents –Interesting links between species learning –And lifetime learning Hybrid algorithms –Evolution with temporal difference learning

6 Links with Biology Evolving sequence classifiers Cell models? Gene regulatory networks? Artificial immune systems? Other ideas?


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