diff --git a/irlc/tests/tests_week01.py b/irlc/tests/tests_week01.py
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+# This file may not be shared/redistributed without permission. Please read copyright notice in the git repo. If this file contains other copyright notices disregard this text.
+from unitgrade import Report
+import irlc
+# from irlc.ex01.frozen_lake import FrozenAgentDownRight
+import gymnasium as gym
+from unitgrade import UTestCase
+from irlc.ex01.inventory_environment import InventoryEnvironment, simplified_train, RandomAgent
+from unitgrade import Capturing2
+import numpy as np
+from gymnasium.envs.toy_text.frozen_lake import RIGHT, DOWN # The down and right-actions; may be relevant.
+from irlc.ex01.pacman_hardcoded import GoAroundAgent, layout
+from irlc.pacman.pacman_environment import PacmanEnvironment
+from irlc import Agent, train
+from irlc.ex01.bobs_friend import BobFriendEnvironment, AlwaysAction_u1, AlwaysAction_u0
+
+
+class Problem1BobsFriend(UTestCase):
+ def test_a_env_basic(self):
+ env = BobFriendEnvironment()
+ s0, _ = env.reset()
+ self.assertEqual(s0, 20, msg="Reset must return the initial state, i.e. the amount of money we start out with")
+
+ def test_a_env_u0(self):
+ env = BobFriendEnvironment()
+ env.reset()
+ s1, r, done, _, _ = env.step(0)
+ self.assertEqual(r, 2, msg="When taking action u0, we must get a reward of 2.")
+ self.assertEqual(s1, 22, msg="When taking action u0, we must end in state x1=22")
+ self.assertEqual(done, True, msg="After taking an action, the environment must terminate")
+
+class Problem2BobsPolicy(UTestCase):
+ def test_a_env_u1(self):
+ env = BobFriendEnvironment()
+ env.reset()
+ s1, r, done, _, _ = env.step(1)
+ print(r)
+ self.assertTrue(r == 12 or r == -20, msg="When taking action u1, we must get a reward of 0 or 12.")
+ self.assertTrue(s1 == 0 or s1 == 32, msg="When taking action u1, we must end in state x1=0 or x1 = 34")
+ self.assertEqual(done, True, msg="After taking an action, the environment must terminate")
+
+ def test_b_always_action_u0(self):
+ env = BobFriendEnvironment()
+ stats, _ = train(env, AlwaysAction_u0(env), num_episodes=1000)
+ avg = np.mean( [stat['Accumulated Reward'] for stat in stats] )
+ self.assertL2(avg, 2, msg="Average reward when we always take action u=0 must be 2.")
+
+ def test_b_always_action_u1(self):
+ env = BobFriendEnvironment()
+ stats, _ = train(env, AlwaysAction_u1(env), num_episodes=10000)
+ avg = np.mean( [stat['Accumulated Reward'] for stat in stats] )
+ self.assertL2(avg, 4, tol=0.5, msg="Average reward when we always take action u=0 must be about 4.")
+
+ def test_b_always_action_u1_starting_200(self):
+ env = BobFriendEnvironment(x0=200)
+ stats, _ = train(env, AlwaysAction_u1(env), num_episodes=10000)
+ avg = np.mean( [stat['Accumulated Reward'] for stat in stats] )
+ self.assertL2(avg, -42, tol=4, msg="Average reward when we always take action u=0 must be about 4.")
+
+ def test_b_always_action_u0_starting_200(self):
+ env = BobFriendEnvironment(x0=200)
+ stats, _ = train(env, AlwaysAction_u0(env), num_episodes=10000)
+ avg = np.mean( [stat['Accumulated Reward'] for stat in stats] )
+ self.assertL2(avg, 20, msg="Average reward when we always take action u=0 must be about 4.")
+
+
+
+class Problem5PacmanHardcoded(UTestCase):
+ """ Test the hardcoded pacman agent """
+ def test_pacman(self):
+ env = PacmanEnvironment(layout_str=layout)
+ agent = GoAroundAgent(env)
+ stats, _ = train(env, agent, num_episodes=1)
+ self.assertEqual(stats[0]['Length'] < 100, True)
+
+
+class Problem6ChessTournament(UTestCase):
+ def test_chess(self):
+ """ Test the correct result in the little chess-tournament """
+ from irlc.ex01.chess import main
+ with Capturing2() as c:
+ main()
+ # Extract the numbers from the console output.
+ print("Numbers extracted from console output was")
+ print(c.numbers)
+ self.assertLinf(c.numbers[-2], 26/33, tol=0.05)
+
+class Problem3InventoryInventoryEnvironment(UTestCase):
+ def test_environment(self):
+ env = InventoryEnvironment()
+ # agent = RandomAgent(env)
+ stats, _ = train(env, Agent(env), num_episodes=2000, verbose=False)
+ avg_reward = np.mean([stat['Accumulated Reward'] for stat in stats])
+ self.assertLinf(avg_reward, tol=0.6)
+
+ def test_random_agent(self):
+ env = InventoryEnvironment()
+ stats, _ = train(env, RandomAgent(env), num_episodes=2000, verbose=False)
+ avg_reward = np.mean([stat['Accumulated Reward'] for stat in stats])
+ self.assertLinf(avg_reward, tol=0.6)
+
+class Problem4InventoryTrain(UTestCase):
+ def test_simplified_train(self):
+ env = InventoryEnvironment()
+ agent = Agent(env)
+ avg_reward_simplified_train = np.mean([simplified_train(env, agent) for i in range(1000)])
+ self.assertLinf(avg_reward_simplified_train, tol=0.5)
+
+# class FrozenLakeTest(UTestCase):
+# def test_frozen_lake(self):
+# env = gym.make("FrozenLake-v1")
+# agent = FrozenAgentDownRight(env)
+# s = env.reset()
+# for k in range(10):
+# self.assertEqual(agent.pi(s, k), DOWN if k % 2 == 0 else RIGHT)
+
+
+class Week01Tests(Report): #240 total.
+ title = "Tests for week 01"
+ pack_imports = [irlc]
+ individual_imports = []
+ questions = [
+ (Problem1BobsFriend, 10),
+ (Problem2BobsPolicy, 10),
+ (Problem3InventoryInventoryEnvironment, 10),
+ (Problem4InventoryTrain, 10),
+ (Problem5PacmanHardcoded, 10),
+ (Problem6ChessTournament, 10), # Week 1: Everything
+ ]
+
+if __name__ == '__main__':
+ from unitgrade import evaluate_report_student
+ evaluate_report_student(Week01Tests())
diff --git a/irlc/tests/unitgrade_data/Problem1BobsFriend.pkl b/irlc/tests/unitgrade_data/Problem1BobsFriend.pkl
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Binary files a/irlc/tests/unitgrade_data/Problem1BobsFriend.pkl and b/irlc/tests/unitgrade_data/Problem1BobsFriend.pkl differ
diff --git a/irlc/tests/unitgrade_data/Problem2BobsPolicy.pkl b/irlc/tests/unitgrade_data/Problem2BobsPolicy.pkl
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Binary files a/irlc/tests/unitgrade_data/Problem2BobsPolicy.pkl and b/irlc/tests/unitgrade_data/Problem2BobsPolicy.pkl differ
diff --git a/irlc/tests/unitgrade_data/Problem3InventoryInventoryEnvironment.pkl b/irlc/tests/unitgrade_data/Problem3InventoryInventoryEnvironment.pkl
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diff --git a/irlc/tests/unitgrade_data/Problem4InventoryTrain.pkl b/irlc/tests/unitgrade_data/Problem4InventoryTrain.pkl
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diff --git a/irlc/tests/unitgrade_data/Problem5PacmanHardcoded.pkl b/irlc/tests/unitgrade_data/Problem5PacmanHardcoded.pkl
index 4b90516956cebe85cdf12481939260cb04f7c151..38874049df6b13f41b7a25f2ca24dd44aaadbe8a 100644
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diff --git a/irlc/tests/unitgrade_data/Problem6ChessTournament.pkl b/irlc/tests/unitgrade_data/Problem6ChessTournament.pkl
index 7bdaed17849541d8d61653d1e5dd5c82f35206e4..aef3d60cea9361a43ac33ec618dd55824929c86b 100644
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