added paralelised experiments

scripts/policy_threaded.py

@@ -0,0 +1,29 @@
+# because multiprocessing Pool cannot run in interactive mode, we put it in a file
+
+from multiprocessing import Pool
+from starter import Agent
+import numpy as np
+
+def make_and_run(init_w):
+    d = 8
+    w = np.full((3,d,d), init_w)
+    a = Agent(side_size=d, weights=w)
+    for e in range(50):
+        a.episode()
+    return a.escape_times
+
+def main():
+    p = Pool(6)
+    # init_w -- 12 examples of each
+    # agents = [0] * 12
+    agents = [0] * 12
+    results = []
+
+    for res in p.map(make_and_run, agents):
+        results.append(res)
+
+    print(results)
+
+if __name__ == "__main__":
+    main()
+

scripts/tau_threaded.py

@@ -0,0 +1,26 @@
+# because multiprocessing Pool cannot run in interactive mode, we put it in a file
+
+from multiprocessing import Pool
+from starter import Agent
+import numpy as np
+
+def make_and_run(tau):
+    a = Agent(tau=tau)
+    for e in range(50):
+        a.episode()
+    return a.escape_times
+
+def main():
+    p = Pool(6)
+    # tau -- 12 examples of each
+    agents = [0.0] * 12
+    results = []
+
+    for res in p.map(make_and_run, agents):
+        results.append(res)
+
+    print(results)
+
+if __name__ == "__main__":
+    main()
+

scripts/threaded.py

@@ -0,0 +1,27 @@
+# because multiprocessing Pool cannot run in interactive mode, we put it in a file
+
+from multiprocessing import Pool
+from starter import Agent
+
+def make_and_run(size):
+    a = Agent(side_size=size)
+    for e in range(60):
+        a.episode()
+        # if 5 times in a row we escape in less than 150 steps
+        if e > 5 and sum(a.escape_times[-5:]) / 5 < 150:
+            break
+    return [size, e]
+
+def main():
+    p = Pool(6)
+    episodes_per_size = []
+
+    # 5 agents of each size from 6 -> 11
+    for res in p.map(make_and_run, sorted(list(range(7,12)) * 5)):
+        episodes_per_size.append(res)
+
+    print(episodes_per_size)
+
+if __name__ == "__main__":
+    main()
+