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 transcript:

Evolutionary Algorithms Simon M. Lucas

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

Idea: fitness evolves over time

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

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

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