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feat: p0 and p1

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zsq259
2024-06-23 00:05:13 +08:00
parent f105d29e25
commit 71975d5889
228 changed files with 11213 additions and 0 deletions
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2
search/test_cases/q4/CONFIG Normal file
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class: "PassAllTestsQuestion"
max_points: "3"

7
search/test_cases/q4/astar_0.solution Normal file
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# This is the solution file for test_cases/q4/astar_0.test.
# This solution is designed to support both right-to-left
# and left-to-right implementations.
solution: "Right Down Down"
expanded_states: "A B D C G"
rev_solution: "Right Down Down"
rev_expanded_states: "A B D C G"

39
search/test_cases/q4/astar_0.test Normal file
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class: "GraphSearchTest"
algorithm: "aStarSearch"
diagram: """
C
^
| 2
2 V 4
*A <----> B -----> [H]
|
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.
"""
# The following section specifies the search problem and the solution.
# The graph is specified by first the set of start states, followed by
# the set of goal states, and lastly by the state transitions which are
# of the form:
# <start state> <actions> <end state> <cost>
graph: """
start_state: A
goal_states: H F
A Right B 2.0
B Right H 4.0
B Down D 1.0
B Up C 2.0
B Left A 2.0
C Down B 2.0
D Right E 2.5
D Down F 2.0
D Left G 1.5
"""

7
search/test_cases/q4/astar_1_graph_heuristic.solution Normal file
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# This is the solution file for test_cases/q4/astar_1_graph_heuristic.test.
# This solution is designed to support both right-to-left
# and left-to-right implementations.
solution: "0 0 2"
expanded_states: "S A D C"
rev_solution: "0 0 2"
rev_expanded_states: "S A D C"

54
search/test_cases/q4/astar_1_graph_heuristic.test Normal file
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class: "GraphSearchTest"
algorithm: "aStarSearch"
diagram: """
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
"""
# The following section specifies the search problem and the solution.
# The graph is specified by first the set of start states, followed by
# the set of goal states, and lastly by the state transitions which are
# of the form:
# <start state> <actions> <end state> <cost>
graph: """
start_state: S
goal_states: G
S 0 A 2.0
S 1 B 3.0
S 2 D 5.0
A 0 C 3.0
A 1 S 2.0
B 0 D 4.0
B 1 S 3.0
C 0 A 3.0
C 1 D 1.0
C 2 G 2.0
D 0 B 4.0
D 1 C 1.0
D 2 G 5.0
D 3 S 5.0
"""
heuristic: """
S 6.0
A 2.5
B 5.25
C 1.125
D 1.0625
G 0
"""

22
search/test_cases/q4/astar_2_manhattan.solution Normal file
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# This is the solution file for test_cases/q4/astar_2_manhattan.test.
# This solution is designed to support both right-to-left
# and left-to-right implementations.
# Number of nodes expanded must be with a factor of 1.1 of the numbers below.
solution: """
West West West West West West West West West South South East East
South South South West West West North West West West West South South
South East East East East East East East South South South South South
South South West West West West West West West West West West West
West West West West West West South West West West West West West West
West West
"""
expanded_nodes: "221"
rev_solution: """
West West West West West West West West West South South East East
South South South West West West North West West West West South South
South East East East East East East East South South South South South
South South West West West West West West West West West West West
West West West West West West South West West West West West West West
West West
"""
rev_expanded_nodes: "221"

27
search/test_cases/q4/astar_2_manhattan.test Normal file
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class: "PacmanSearchTest"
algorithm: "aStarSearch"
# The following specifies the layout to be used
layoutName: "mediumMaze"
layout: """
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% P%
% %%%%%%%%%%%%%%%%%%%%%%% %%%%%%%% %
% %% % % %%%%%%% %% %
% %% % % % % %%%% %%%%%%%%% %% %%%%%
% %% % % % % %% %% %
% %% % % % % % %%%% %%% %%%%%% %
% % % % % % %% %%%%%%%% %
% %% % % %%%%%%%% %% %% %%%%%
% %% % %% %%%%%%%%% %% %
% %%%%%% %%%%%%% %% %%%%%% %
%%%%%% % %%%% %% % %
% %%%%%% %%%%% % %% %% %%%%%
% %%%%%% % %%%%% %% %
% %%%%%% %%%%%%%%%%% %% %% %
%%%%%%%%%% %%%%%% %
%. %%%%%%%%%%%%%%%% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
"""
leewayFactor: "1.1"
heuristic: "manhattanHeuristic"

7
search/test_cases/q4/astar_3_goalAtDequeue.solution Normal file
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# This is the solution file for test_cases/q4/astar_3_goalAtDequeue.test.
# This solution is designed to support both right-to-left
# and left-to-right implementations.
solution: "1:A->B 0:B->C 0:C->G"
expanded_states: "A B C"
rev_solution: "1:A->B 0:B->C 0:C->G"
rev_expanded_states: "A B C"

29
search/test_cases/q4/astar_3_goalAtDequeue.test Normal file
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class: "GraphSearchTest"
algorithm: "aStarSearch"
diagram: """
1 1 1
*A ---> B ---> C ---> [G]
| ^
| 10 |
\---------------------/
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.
"""
graph: """
start_state: A
goal_states: G
A 0:A->G G 10.0
A 1:A->B B 1.0
B 0:B->C C 1.0
C 0:C->G G 1.0
"""
# We only care about the solution, not the expansion order.
exactExpansionOrder: "False"

7
search/test_cases/q4/graph_backtrack.solution Normal file
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# This is the solution file for test_cases/q4/graph_backtrack.test.
# This solution is designed to support both right-to-left
# and left-to-right implementations.
solution: "1:A->C 0:C->G"
expanded_states: "A B C D"
rev_solution: "1:A->C 0:C->G"
rev_expanded_states: "A B C D"

32
search/test_cases/q4/graph_backtrack.test Normal file
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class: "GraphSearchTest"
algorithm: "aStarSearch"
diagram: """
B
^
|
*A --> C --> G
|
V
D
A is the start state, G is the goal. Arrows mark
possible state transitions. This tests whether
you extract the sequence of actions correctly even
if your search backtracks. If you fail this, your
nodes are not correctly tracking the sequences of
actions required to reach them.
"""
# The following section specifies the search problem and the solution.
# The graph is specified by first the set of start states, followed by
# the set of goal states, and lastly by the state transitions which are
# of the form:
# <start state> <actions> <end state> <cost>
graph: """
start_state: A
goal_states: G
A 0:A->B B 1.0
A 1:A->C C 2.0
A 2:A->D D 4.0
C 0:C->G G 8.0
"""

7
search/test_cases/q4/graph_manypaths.solution Normal file
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# This is the solution file for test_cases/q4/graph_manypaths.test.
# This solution is designed to support both right-to-left
# and left-to-right implementations.
solution: "1:A->C 0:C->D 1:D->F 0:F->G"
expanded_states: "A B1 C B2 D E1 F E2"
rev_solution: "1:A->C 0:C->D 1:D->F 0:F->G"
rev_expanded_states: "A B1 C B2 D E1 F E2"

39
search/test_cases/q4/graph_manypaths.test Normal file
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class: "GraphSearchTest"
algorithm: "aStarSearch"
diagram: """
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.
"""
# The following section specifies the search problem and the solution.
# The graph is specified by first the set of start states, followed by
# the set of goal states, and lastly by the state transitions which are
# of the form:
# <start state> <actions> <end state> <cost>
graph: """
start_state: A
goal_states: G
A 0:A->B1 B1 1.0
A 1:A->C C 2.0
A 2:A->B2 B2 4.0
B1 0:B1->C C 8.0
B2 0:B2->C C 16.0
C 0:C->D D 32.0
D 0:D->E1 E1 64.0
D 1:D->F F 128.0
D 2:D->E2 E2 256.0
E1 0:E1->F F 512.0
E2 0:E2->F F 1024.0
F 0:F->G G 2048.0
"""