From 583ddeae93809b2c074e5d2320def49b19424dc9 Mon Sep 17 00:00:00 2001
From: Brendan Hansen <brendan.f.hansen@gmail.com>
Date: Fri, 1 Mar 2019 00:20:55 -0600
Subject: [PATCH] changed model of neural network

---
 nn/data.lua | 14 +++++++++++---
 nn/nn.lua   | 17 +++++++++--------
 2 files changed, 20 insertions(+), 11 deletions(-)

diff --git a/nn/data.lua b/nn/data.lua
index b05a2af..061bdaa 100644
--- a/nn/data.lua
+++ b/nn/data.lua
@@ -92,7 +92,12 @@ function saveNeuralNetwork(network, file_path)
 
 	for l = 1, numLayers do
 		local layer = network.network[l]
-		file:write(tostring(layer.bias) .. "\n")
+
+		for n = 1, #layer.neurons do
+			file:write(tostring(bias) .. ' ')
+		end
+
+		file:write("\n")
 
 		for n = 1, #layer.neurons do
 			local neuron = layer.neurons[n]
@@ -127,12 +132,15 @@ function loadNeuralNetwork(file_path)
 
 	for l = 1, numLayers do
 		log.log(log.LOG_INFO, "Reading layer " .. l)
-		local bias = file:read("*number")
-		network.network[l].bias = bias
 
 		local upper = layerCount[l - 1]
 		if upper == nil then upper = layerCount[l] end
 
+		for n = 1, layerCount[l] do
+			local bias = file:read("*number")
+			network.network[l].neurons[n].bias = bias
+		end
+
 		for n = 1, layerCount[l] do
 			for w = 1, upper do
 				local weight = file:read("*number")
diff --git a/nn/nn.lua b/nn/nn.lua
index 102b98c..c98608e 100644
--- a/nn/nn.lua
+++ b/nn/nn.lua
@@ -5,18 +5,21 @@ function Neuron:init(input_count)
 	self.value = 0
 	self.delta = 0
 	self.weights = {}
+	self.bias = math.random() * 1 - .5
 	for i in range(1, input_count) do
 		self.weights[i] = math.random() * 1 - .5 -- Initialize to random weights
 	end
 end
 
-function Neuron:activate(inputs, bias)
+function Neuron:activate(inputs)
 	local weights = self.weights
+
+	local activation = self.bias
 	for i = 1, #weights do
-		bias = bias + (weights[i] * inputs[i])
+		activation = activation + (weights[i] * inputs[i])
 	end
 
-	self.value = bias / (2 + 2 * math.abs(bias)) + 0.5
+	self.value = activation / (2 + 2 * math.abs(activation)) + 0.5
 end
 
 Layer = class()
@@ -28,8 +31,6 @@ function Layer:init(neuron_count, input_count)
 	for i = 1, neuron_count do
 		self.neurons[i] = Neuron(input_count)
 	end
-
-	self.bias = math.random()
 end
 
 NeuralNetwork = class()
@@ -59,9 +60,8 @@ function NeuralNetwork:activate(inputs)
 			inputs[j] = prevCells[j].value
 		end
 
-		local bias = self.network[i].bias
 		for j = 1, #cells do
-			cells[j]:activate(inputs, bias)
+			cells[j]:activate(inputs)
 		end
 	end
 end
@@ -96,10 +96,11 @@ function NeuralNetwork:back_propagate(inputs, outputs)
 	end
 
 	for i = 2, numLayers do
-		self.network[i].bias = self.network[i].neurons[#self.network[i].neurons].delta * learningRate
 		for j = 1, #self.network[i].neurons do
+			self.network[i].neurons[j].bias = self.network[i].neurons[j].bias + self.network[i].neurons[j].delta * learningRate
 			for k = 1, #self.network[i].neurons[j].weights do
 				local weights = self.network[i].neurons[j].weights
+
 				weights[k] = weights[k] + self.network[i].neurons[j].delta * learningRate * self.network[i - 1].neurons[k].value
 			end
 		end
-- 
2.25.1