本文整理汇总了Python中terrain.Terrain.is_goal_node方法的典型用法代码示例。如果您正苦于以下问题：Python Terrain.is_goal_node方法的具体用法？Python Terrain.is_goal_node怎么用？Python Terrain.is_goal_node使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类terrain.Terrain的用法示例。
在下文中一共展示了Terrain.is_goal_node方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: Agent
# 需要导入模块: from terrain import Terrain [as 别名]
# 或者: from terrain.Terrain import is_goal_node [as 别名]
class Agent(object):
"""
Class to handle decisions about getting to the goal.
:param: Terrain - the terrain on which the agent is navigating
:param: Heuristic - the difficulty level of the heuristic
"""
def __init__(self, terrain, heuristic):
self.terrain = Terrain(terrain)
self.directions = {'N': (0, -1),
'E': (1, 0),
'S': (0, 1),
'W': (-1, 0)}
self.start_node = Node(self.terrain.get_start_position(), 'N', 0)
# Push our start position onto the heap
self.search_heap = SearchHeap(initial=[self.start_node],
g_func=lambda node: node.g,
h_func=heuristic,
goal=self.terrain.get_goal_position())
self.visited = []
self.position = list(self.terrain.get_start_position())
self.facing = 'N'
self.action_costs = {'forward': lambda cost: -cost,
'bash': lambda cost: -3,
'turn': lambda cost: -ceil(float(cost)/float(3)),
'demolish': lambda cost: -4}
print "goal position:"
print self.terrain.get_goal_position()
def a_star_search(self):
"""A* search for the goal"""
while self.search_heap.is_not_empty():
node = self.search_heap.pop()
# add the node to self.visited to show we visited it
self.visited.append(node)
"""
print "current position:"
print node.position
print "current direction:"
print node.direction
print "node g score:"
print node.g
"""
if self.terrain.is_goal_node(node):
# TODO: make it return the path to the goal
# as a sequence of nodes
print "Score of the path:"
print node.g + 100
print "Number of actions required to reach the goal:"
print node.depth
print "Number of nodes expanded:"
print len(self.visited)
break
for action, neighbor in self.get_search_neighbors(node).iteritems():
last_time_visited = self.has_been_visited_already(neighbor)
if last_time_visited is None and self.terrain.node_inside_terrain(neighbor):
neighbor.g = self.assign_g_cost(neighbor, node, self.terrain, action)
self.search_heap.push(neighbor)
def get_search_neighbors(self, node):
"""Returns a list of node leaves from the given node."""
# These things create nodes
turn_left = Node(position=node.position,
direction=self.turn_left(node),
depth=node.depth + 1)
turn_right = Node(position=node.position,
direction=self.turn_right(node),
depth=node.depth + 1)
move_forward = Node(position=self.forward(node),
direction=node.direction,
depth=node.depth + 1)
bash_and_forward = Node(position=self.bash_and_forward(node),
direction=node.direction,
depth=node.depth + 1)
# return the nodes
return {'turn_left': turn_left,
'turn_right': turn_right,
'move_forward': move_forward,
'bash_and_forward': bash_and_forward}
def assign_g_cost(self, node, parent, terrain, action):
if 'turn' in action:
# Update the g costs of the nodes
return(parent.g +
self.action_costs['turn'](
self.terrain.get_cost_from_tuple(
node.position)))
elif action == 'move_forward':
return parent.g + self.action_costs['forward'](
self.terrain.get_cost_from_tuple(
node.position))
else:
return parent.g + self.action_costs['bash'](0) + self.action_costs['forward'](
self.terrain.get_cost_from_tuple(
node.position))
def forward(self, node):
"""The rules to move forward"""
new_pos = (node.position[0] + self.directions[node.direction][0],
#.........这里部分代码省略.........