def search_solution_dfs(state: list,
problem: Problem,
threshold=1000,
interactive=False) -> list:
""" Search the sequence of actions that leads to the goal state and puts
it on self.solve_stack variable
"""
# keep up a history of most recent states viseted
history = []
# create the root node with the current state
root = Node(state, 'None', None)
frontier = [root] # create the frontier stack and append the root to it
# holds the stack sequence of actions the agent is going to do to
# achieve his goal
solve_stack = []
while frontier: # while frontier is not empty
node = frontier.pop(-1) # pop the last node on the frontier
# if this node is the goal state
if node.content == problem.define_goal(state):
# append all the nodes parents while it's not the root node
solve_stack.append(node)
while node.parent != None and node.parent.parent != None:
node = node.parent
solve_stack.append(node)
# since we found a solution
print(f'Steps needed: {len(solve_stack)}')
return solve_stack
# if we've crossed the threshold and there is any node on the frontier
if node.depth >= threshold and frontier:
continue
# if the state is not the goal state
if node.content not in history:
problem.apply_operators(node, frontier)
history.append(node.content)
if len(history) > 100:
history.pop(0)
# if we are doing a interactive search
if interactive and not frontier:
print(f'No answer was found on a node of depth less than '
f'{threshold}, We are gonna keep looking')
frontier = [root]
threshold += 2
history.clear()
continue
elif not interactive and not frontier:
print(f'No answer was found on a node of depth less than \
{threshold}')
return []
# if we don't found any soluction
return []
def search_solution_bfs(state: list,
problem: Problem,
keep_history=False,
history_len=100) -> list:
"" """ Search the sequence of actions that leads to the goal state and puts
it on self.solve_stack variable
"""
# keep up a history of most recent states viseted
history = []
# create the root node with the current state
root = Node(state, 'None', None)
frontier = [root] # create the frontier queue and append the root to it
# holds the stack sequence of actions the agent is going to do to
# achieve his goal
solve_stack = []
while frontier: # while frontier is not empty
node = frontier.pop(0) # pop the first node on the frontier
# if this node is the goal state
if node.content == problem.define_goal(state):
# append all the nodes parents while it's not the root node
solve_stack.append(node)
while node.parent != None and node.parent.parent != None:
node = node.parent
solve_stack.append(node)
# since we found a solution
print(f'Steps needed: {len(solve_stack)}')
return solve_stack
# if the state is not the goal state and we keep history
if keep_history:
# if the state is not in the history
if node.content not in history:
problem.apply_operators(node, frontier)
history.append(node.content)
if len(history) > history_len:
history.pop(0)
else:
problem.apply_operators(node, frontier)
# if we don't found any soluction
return []
