add car racing sim and first geno to phenotype mapper experiment.

experiments/simple_nn/simplest_nn.py

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+import random
+import math
+import threading
+import queue
+
+
+class Neuron(threading.Thread):
+    def __init__(self, weights, neuron_queue, actuator_queue):
+        super().__init__()
+        self.weights = weights
+        self.neuron_queue = neuron_queue
+        self.actuator_queue = actuator_queue
+        self.running = True
+
+    def dot(self, input_vector):
+        acc = sum(i * w for i, w in zip(input_vector, self.weights[:-1]))
+        return acc + self.weights[-1]
+
+    def run(self):
+        while self.running:
+            try:
+                message = self.neuron_queue.get(timeout=1)
+                if message[0] == "forward":
+                    input_vector = message[1]
+                    print("**** Thinking ****")
+                    print(f"Input: {input_vector}")
+                    print(f"With Weights: {self.weights}")
+
+                    dot_product = self.dot(input_vector)
+                    output = [math.tanh(dot_product)]
+
+                    self.actuator_queue.put(("forward", output))
+                elif message[0] == "terminate":
+                    self.running = False
+            except queue.Empty:
+                continue
+
+
+class Sensor(threading.Thread):
+    def __init__(self, sensor_queue, neuron_queue):
+        super().__init__()
+        self.sensor_queue = sensor_queue
+        self.neuron_queue = neuron_queue
+        self.running = True
+
+    def run(self):
+        while self.running:
+            try:
+                message = self.sensor_queue.get(timeout=1)
+                if message == "sync":
+                    sensory_signal = [random.uniform(0, 1), random.uniform(0, 1)]
+                    print("**** Sensing ****")
+                    print(f"Signal from the environment: {sensory_signal}")
+
+                    self.neuron_queue.put(("forward", sensory_signal))
+                elif message == "terminate":
+                    self.running = False
+            except queue.Empty:
+                continue
+
+
+class Actuator(threading.Thread):
+    def __init__(self, actuator_queue):
+        super().__init__()
+        self.actuator_queue = actuator_queue
+        self.running = True
+
+    def pts(self, control_signal):
+        print("**** Acting ****")
+        print(f"Using: {control_signal} to act on the environment.")
+
+    def run(self):
+        while self.running:
+            try:
+                message = self.actuator_queue.get(timeout=1)
+                if message[0] == "forward":
+                    control_signal = message[1]
+                    self.pts(control_signal)
+                elif message[0] == "terminate":
+                    self.running = False
+            except queue.Empty:
+                continue
+
+
+class Cortex(threading.Thread):
+    def __init__(self, sensor_queue, neuron_queue, actuator_queue):
+        super().__init__()
+        self.sensor_queue = sensor_queue
+        self.neuron_queue = neuron_queue
+        self.actuator_queue = actuator_queue
+        self.running = True
+
+    def run(self):
+        while self.running:
+            command = input("amna> ").strip()
+            if command == "sense_think_act":
+                self.sensor_queue.put("sync")
+            elif command == "terminate":
+                self.sensor_queue.put("terminate")
+                self.neuron_queue.put(("terminate",))
+                self.actuator_queue.put(("terminate",))
+                self.running = False
+            else:
+                print("Unknown command. Please use 'sense_think_act' or 'terminate'.")
+        print("Cortex terminated.")
+
+
+if __name__ == "__main__":
+    sensor_queue = queue.Queue()
+    neuron_queue = queue.Queue()
+    actuator_queue = queue.Queue()
+
+    # initialize weights (including bias)
+    weights = [random.uniform(-0.5, 0.5) for _ in range(2)] + [random.uniform(-0.5, 0.5)]  # Zwei Gewichte + Bias
+
+    sensor = Sensor(sensor_queue, neuron_queue)
+    neuron = Neuron(weights, neuron_queue, actuator_queue)
+    actuator = Actuator(actuator_queue)
+
+    sensor.start()
+    neuron.start()
+    actuator.start()
+
+    cortex = Cortex(sensor_queue, neuron_queue, actuator_queue)
+    cortex.start()
+
+    cortex.join()
+
+    sensor.join()
+    neuron.join()
+    actuator.join()
+
+    print("System terminated.")