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.
"""

# A simple graph-search problem, in which the agent can move east and west,
# where moving east takes the agent directly to the goal at a high cost, and
# moving west takes him slowly to the goal at a low cost. In queue-based
# search algorithms, if you incorrectly check for goal states when producing 
# successors, the agent will go east. If you correctly check for goal states 
# only when a node is being dequeued/expanded, the agent will move west.
graph: """
start_state: A
goal_states: G
A East G 10.0
A West B 1.0
B West C 1.0
C West D 1.0
"""
# We only care about the solution, not the expansion order.
exactExpansionOrder: "False"