A neural network has proved better than human experts at pinpointing the sources of stone used by ancient Melanesian peoples to make tools. The network is so good at this task, called provenancing, that its Australian designers believe it may ultimately replace existing procedures for classifying tools and other archaeological remains from around the world.
This is the first time that neural networks - computer simulations of the way that neurons in the brain work - have been used for this purpose. Archaeometrists who locate sources of stone used by the ancients to make their 'tool kits', have traditionally relied on experience and complex statistical analyses to make their judgements.
Neural networks are particularly good at picking out associations between items of data. This makes them good at recognising patterns, and makes them able to 'learn' from experience simply by strengthening the associations. Simple neural networks are already used for ...
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