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author | sanine <sanine.not@pm.me> | 2023-10-13 12:05:34 -0500 |
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committer | sanine <sanine.not@pm.me> | 2023-10-13 12:05:34 -0500 |
commit | e257d91ac1a9504a4f058c124fe315034fae2b10 (patch) | |
tree | bfa28b244225f763cd0924cfa582bb7466642b29 /src/mind/README.md | |
parent | 1ad77cbdadb6e8c389c128b0f95907505e1b22ca (diff) |
README.md
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diff --git a/src/mind/README.md b/src/mind/README.md new file mode 100644 index 0000000..1ece125 --- /dev/null +++ b/src/mind/README.md @@ -0,0 +1,37 @@ +mind +==== + +This module is used to create arbitrary stateful neural networks. + +The only export is the following function: + +``` +network(input_count, internal_count, output_count, weight_max = 4 : number) +``` + +This function returns an object that represents a neural network with `input_count` input neurons, +`internal_count` internal (and stateful) neurons, and `output_count` output neurons. `max_weight` determines +the maximum absolute value allowed for connection weights. + +A network object has two methods: + +``` +connect(source, sink, weight : number) +``` + +This method returns a new network object that is an exact copy of the original, except with a new +connection between the neuron indexed by `source` and `sink`, with weight `weight`. Neuron indices +are zero-indexed, and span all neurons, first the inputs, then the internal neurons, and finally the outputs. +An error will be thrown if `source` is in the range of output neurons or if `sink` is in the range of input +neurons. + + +``` +compute(inputs, state : array[number]) +``` + +This method returns a tuple `[output, newState]`, where `output` is an array of `output_count` values +corresponding to the output neuron's computed values, and `newState` is the new state of the internal neurons. + +`input` must be an array of numbers with length equal to `input_count`, and `state` must be an array of numbers +with length equal to `internal_count` or an error will be raised. |