{'teams': {0: {'team_name': 'search', 'agent': 'search.py', 'url': 'https://github.com/COMP90054-2025-Semester1/assignment-1-search-nickdurham1.git', 'commit_id': 'b33268906d36c54307b6c043dc3d0a387c8556db', 'git_status': True, 'comments': 'N/A', 'submitted_time': '24/03/2025 17:58:23', 'copy_files': True}}} before grades Starting on 3-24 at 7:01:53 after grades Question part1 ============== *** Search time: 0:00:01.305037 *** PASS: marking/part1/food_heuristic_grade_tricky.test *** expanded nodes: 4137 *** thresholds: [15000, 12500, 10000, 4200] *** Search time: 0:00:01.758802 *** FAIL: marking/part1/hidden_heuristic_grade.test *** expanded nodes: 6726 *** thresholds: [18000, 17000, 7500, 6500] ### Question part1: 1.80/2 ### Question part2 ============== *** FAIL: marking/part2/graph_manypaths.test *** graph: *** B1 E1 *** ^ \ ^ \ *** / V / V *** *A --> C --> D --> F --> [G] *** \ ^ \ ^ *** V / V / *** B2 E2 *** *** A is the start state, G is the goal. Arrows mark *** possible state transitions. This graph has multiple *** paths to the goal, where nodes with the same state *** are added to the fringe multiple times before they *** are expanded. *** student solution: ['2:A->B2', '0:B2->C', '0:C->D', '2:D->E2', '0:E2->F', '0:F->G'] *** student expanded_states: ['A', 'A', 'B1', 'B1', 'C', 'C', 'D', 'D', 'E1', 'E1', 'F', 'F', 'A', 'A', 'B2', 'B2', 'C', 'C', 'D', 'D', 'E2', 'E2', 'F', 'F'] *** *** correct solution: ['1:A->C', '0:C->D', '1:D->F', '0:F->G'] *** correct expanded_states: ['A', 'B1', 'C', 'D', 'E1', 'F', 'A', 'B2', 'C', 'D', 'E2', 'F', 'A', 'B1', 'C', 'D', 'E1', 'F', 'A', 'B2', 'C', 'D', 'F', 'A', 'B1', 'C', 'D', 'F', 'A', 'B2', 'C', 'D', 'F', 'A', 'B1', 'C', 'D', 'F', 'A', 'C', 'D', 'F', 'A', 'C', 'D', 'F'] *** correct rev_solution: ['1:A->C', '0:C->D', '1:D->F', '0:F->G'] *** correct rev_expanded_states: ['A', 'B1', 'C', 'D', 'E1', 'F', 'A', 'B2', 'C', 'D', 'E2', 'F', 'A', 'B1', 'C', 'D', 'E1', 'F', 'A', 'B2', 'C', 'D', 'F', 'A', 'B1', 'C', 'D', 'F', 'A', 'B2', 'C', 'D', 'F', 'A', 'B1', 'C', 'D', 'F', 'A', 'C', 'D', 'F', 'A', 'C', 'D', 'F'] *** FAIL: marking/part2/lrta_0.test *** graph: *** C *** ^ *** | 2 *** 2 V 4 *** *A <----> B -----> [H] *** ^ *** 1 | *** 1.5 V 2.5 *** G <----> D <----> E *** | *** 2 | *** V *** [F] *** *** A is the start state, F and H is the goal. Arrows mark possible state *** transitions. The number next to the arrow is the cost of that transition. *** student solution: ['Right', 'Up', 'Down', 'Down', 'Down'] *** student expanded_states: ['A', 'A', 'B', 'B', 'D', 'D', 'G', 'G', 'D', 'D', 'A', 'A', 'B', 'B', 'C', 'C', 'B', 'B', 'D', 'D'] *** *** correct solution: ['Right', 'Down', 'Down'] *** correct expanded_states: ['A', 'B', 'D', 'G', 'D', 'A', 'B', 'C', 'B', 'D', 'A', 'B', 'D', 'A', 'B', 'D'] *** correct rev_solution: ['Right', 'Down', 'Down'] *** correct rev_expanded_states: ['A', 'B', 'D', 'G', 'D', 'B', 'C', 'B', 'D', 'A', 'B', 'D', 'A', 'B', 'D'] *** FAIL: marking/part2/lrta_1_good_heuristic.test *** graph: *** 3 3 3 *** *A ---- B ---- C ---- [G] *** | ^ *** | 1 1 10 | *** \----- D ---- E -----/ *** *** A is the start state, G is the goal. Arrows mark possible state *** transitions. The number next to the arrow is the cost of that transition. *** *** If you fail this test case, you may be incorrectly testing if a node is a goal *** before adding it into the queue, instead of testing when you remove the node *** from the queue. See the algorithm pseudocode in lecture. *** student solution: ['1:A->B', '0:B->C', '0:C->G'] *** student expanded_states: ['A', 'A', 'B', 'B', 'C', 'C', 'A', 'A', 'B', 'B', 'C', 'C'] *** *** correct solution: ['1:A->B', '0:B->C', '0:C->G'] *** correct expanded_states: ['A', 'B', 'C', 'A', 'B', 'C', 'A', 'D', 'E', 'D', 'E', 'A', 'B', 'C', 'A', 'B', 'C'] *** correct rev_solution: ['1:A->B', '0:B->C', '0:C->G'] *** correct rev_expanded_states: ['A', 'B', 'C', 'A', 'B', 'C', 'A', 'D', 'E', 'D', 'A', 'B', 'C', 'A', 'B', 'C'] *** FAIL: marking/part2/lrta_2_bad_heuristic.test *** graph: *** 3 3 3 *** *A ---- B ---- C ---- [G] *** | ^ *** | 1 1 10 | *** \----- D ---- E -----/ *** *** A is the start state, G is the goal. Arrows mark possible state *** transitions. The number next to the arrow is the cost of that transition. *** *** If you fail this test case, you may be incorrectly testing if a node is a goal *** before adding it into the queue, instead of testing when you remove the node *** from the queue. See the algorithm pseudocode in lecture. *** student solution: ['0:A->D', '0:D->E', '0:E->D', '0:D->E', '0:E->D', '0:D->E', '0:E->D', '0:D->E', '0:E->D', '1:D->A', '1:A->B', '0:B->C', '0:C->G'] *** student expanded_states: ['A', 'A', 'D', 'D', 'E', 'E', 'D', 'D', 'E', 'E', 'D', 'D', 'E', 'E', 'D', 'D', 'E', 'E', 'D', 'D', 'A', 'A', 'B', 'B', 'C', 'C'] *** *** correct solution: ['1:A->B', '0:B->C', '0:C->G'] *** correct expanded_states: ['A', 'D', 'E', 'D', 'E', 'D', 'E', 'D', 'E', 'D', 'A', 'B', 'C', 'A', 'B', 'C'] *** correct rev_solution: ['1:A->B', '0:B->C', '0:C->G'] *** correct rev_expanded_states: ['A', 'D', 'E', 'D', 'E', 'D', 'E', 'D', 'E', 'D', 'A', 'B', 'C', 'A', 'B', 'C'] *** FAIL: marking/part2/lrta_3_hidden.test *** graph: *** 2 3 2 *** S --- A --- C ---> G *** | \ / ^ *** 3 | \ 5 / 1 / *** | \ / / *** B --- D -------/ *** 4 5 *** *** S is the start state, G is the goal. Arrows mark possible state *** transitions. The number next to the arrow is the cost of that transition. *** *** The heuristic value of each state is: *** S 6.0 *** A 2.5 *** B 5.25 *** C 1.125 *** D 1.0625 *** G 0 *** student solution: ['2', '1', '2'] *** student expanded_states: ['S', 'S', 'A', 'A', 'C', 'C', 'S', 'S', 'D', 'D', 'C', 'C'] *** *** correct solution: ['0', '0', '2'] *** correct expanded_states: ['S', 'A', 'C', 'S', 'D', 'C', 'S', 'A', 'C', 'S', 'A', 'C', 'S', 'A', 'C'] *** correct rev_solution: ['0', '0', '2'] *** correct rev_expanded_states: ['S', 'A', 'C', 'S', 'D', 'C', 'S', 'A', 'C', 'S', 'A', 'C', 'S', 'A', 'C'] *** PASS: marking/part2/lrta_4_hidden.test *** solution: ['1:A->B', '0:B->C', '0:C->G'] *** expanded_states: ['A', 'A', 'B', 'B', 'C', 'C', 'A', 'A', 'B', 'B', 'C', 'C'] ### Question part2: 0.50/3 ### Question part3 ============== *** FAIL: Exception raised: lrtakStarTrial() missing 1 required positional argument: 'k' *** *** Traceback (most recent call last): *** File "/code/assignment1/code_base/grading.py", line 79, in grade *** util.TimeoutFunction(getattr(gradingModule, q), 2000)(self) # Call the question's function *** File "/code/assignment1/code_base/util.py", line 663, in __call__ *** result = self.function(*args, **keyArgs) *** File "autograder.py", line 306, in *** return lambda grades: question.execute(grades) *** File "/code/assignment1/code_base/testClasses.py", line 143, in execute *** grades.addPoints([f(grades) for _, f in self.testCases].count(True) * multiplier) *** File "/code/assignment1/code_base/testClasses.py", line 143, in *** grades.addPoints([f(grades) for _, f in self.testCases].count(True) * multiplier) *** File "autograder.py", line 300, in *** return lambda grades: testCase.execute(grades, moduleDict, solutionDict) *** File "/code/assignment1/code_base/searchTestClasses.py", line 321, in execute *** solution, expanded_states, error = self.getSolInfo(search) *** File "/code/assignment1/code_base/searchTestClasses.py", line 304, in getSolInfo *** solution = alg(problem) *** File "/code/assignment1/code_base/search.py", line 342, in lrtakStarSearch *** path = lrtakStarTrial(problem, learningHeuristic) # doing lrta trial and returns a path *** TypeError: lrtakStarTrial() missing 1 required positional argument: 'k' *** ### Question part3: 0.00/2 ### Finished at 7:01:56 Provisional grades ================== Question part1: 1.80/2 Question part2: 0.50/3 Question part3: 0.00/2 ------------------ Total passed test cases: 2.30/7