Posts Tagged genetic algorithms
There’s been a lot of buzz recently on reddit and HN about genetic algorithms. Some impressive new demos have surfaced and I’d like to take this opportunity to review some of the cool things people have done with genetic algorithms, a fascinating subfield of evolutionary computing / machine learning (which is itself a part of the broader study of artificial intelligence (ah how academics love to classify things (and nest parentheses (especially computer scientists)))).
So here’s my top five evolutionary scripts:
This article works through the creation of a ‘toy’ genetic algorithm which starts with a few hundred random strings and evolves towards the phrase “Hello World!”. It’s a toy example because we know in advance what the optimum solution is – the phrase “Hello World!” – but it provides a nice simple introduction to evolutionary algorithms.
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Machine learning is a fascinating discipline. Often inspired by natural processes, it can produce astounding results in a wide range of applications. Modern web search is underpinned by ML techniques such as clustering and statistical text processing. Computer games make use of evolutionary algorithms to produce better artificial enemies. Your camera probably has face detection in it for aiding auto-focus. Machine learning is key to making our technology better and our lives easier.
Today I’m going to give a very brief and incomplete overview of machine learning technologies and applications. There are three broad types of machine learning: Categorisation, Optimisation and Prediction.