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168 changes: 95 additions & 73 deletions code/pacman/search/search.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,21 @@
# search.py
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<title>search.py</title>
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<h3>search.py (<a href="http://ai.berkeley.edu/projects/release/search/v1/001/search.zip">original</a>)</h3>
<hr>
<pre>
<span style="color: green; font-style: italic"># search.py
# ---------
# Licensing Information: You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
Expand All @@ -12,90 +29,68 @@
# Pieter Abbeel (pabbeel@cs.berkeley.edu).


"""
</span><span style="color: darkred">"""
In search.py, you will implement generic search algorithms which are called by
Pacman agents (in searchAgents.py).
"""

import util
</span><span style="color: blue; font-weight: bold">import </span>util

class SearchProblem:
"""
<span style="color: blue; font-weight: bold">class </span>SearchProblem<span style="font-weight: bold">:
</span><span style="color: darkred">"""
This class outlines the structure of a search problem, but doesn't implement
any of the methods (in object-oriented terminology: an abstract class).

You do not need to change anything in this class, ever.
"""

def getStartState(self):
"""
</span><span style="color: blue; font-weight: bold">def </span>getStartState<span style="font-weight: bold">(</span><span style="color: blue">self</span><span style="font-weight: bold">):
</span><span style="color: darkred">"""
Returns the start state for the search problem.
"""
util.raiseNotDefined()
</span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

def isGoalState(self, state):
"""
</span><span style="color: blue; font-weight: bold">def </span>isGoalState<span style="font-weight: bold">(</span><span style="color: blue">self</span><span style="font-weight: bold">, </span>state<span style="font-weight: bold">):
</span><span style="color: darkred">"""
state: Search state

Returns True if and only if the state is a valid goal state.
"""
util.raiseNotDefined()
</span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

def getSuccessors(self, state):
"""
</span><span style="color: blue; font-weight: bold">def </span>getSuccessors<span style="font-weight: bold">(</span><span style="color: blue">self</span><span style="font-weight: bold">, </span>state<span style="font-weight: bold">):
</span><span style="color: darkred">"""
state: Search state

For a given state, this should return a list of triples, (successor,
action, stepCost), where 'successor' is a successor to the current
state, 'action' is the action required to get there, and 'stepCost' is
the incremental cost of expanding to that successor.
"""
util.raiseNotDefined()
</span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

def getCostOfActions(self, actions):
"""
</span><span style="color: blue; font-weight: bold">def </span>getCostOfActions<span style="font-weight: bold">(</span><span style="color: blue">self</span><span style="font-weight: bold">, </span>actions<span style="font-weight: bold">):
</span><span style="color: darkred">"""
actions: A list of actions to take

This method returns the total cost of a particular sequence of actions.
The sequence must be composed of legal moves.
"""
util.raiseNotDefined()
</span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()


def tinyMazeSearch(problem):
"""
</span><span style="color: blue; font-weight: bold">def </span>tinyMazeSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">):
</span><span style="color: darkred">"""
Returns a sequence of moves that solves tinyMaze. For any other maze, the
sequence of moves will be incorrect, so only use this for tinyMaze.
"""
from game import Directions
s = Directions.SOUTH
w = Directions.WEST
return [s, s, w, s, w, w, s, w]

</span><span style="color: blue; font-weight: bold">from </span>game <span style="color: blue; font-weight: bold">import </span>Directions
s <span style="font-weight: bold">= </span>Directions<span style="font-weight: bold">.</span>SOUTH
w <span style="font-weight: bold">= </span>Directions<span style="font-weight: bold">.</span>WEST
<span style="color: blue; font-weight: bold">return </span><span style="font-weight: bold">[</span>s<span style="font-weight: bold">, </span>s<span style="font-weight: bold">, </span>w<span style="font-weight: bold">, </span>s<span style="font-weight: bold">, </span>w<span style="font-weight: bold">, </span>w<span style="font-weight: bold">, </span>s<span style="font-weight: bold">, </span>w<span style="font-weight: bold">]

def nullHeuristic(state, problem=None):
"""
A heuristic function estimates the cost from the current state to the nearest
goal in the provided SearchProblem. This heuristic is trivial.
"""
return 0

def generalPurposeSearch(problem, stack, heuristic=nullHeuristic):
marked = set()
stack.push(([], problem.getStartState(), 0, 0))
while not stack.isEmpty():
(directions, nextState, costSoFar, stateValue) = stack.pop()
if problem.isGoalState(nextState):
return directions
if nextState not in marked:
successors = problem.getSuccessors(nextState)
for (successor, direction, cost) in successors:
hCost = heuristic(successor, problem)
stack.push((directions + [direction], successor, costSoFar + cost, costSoFar + cost + hCost))
marked.add(nextState)

def depthFirstSearch(problem):
"""
</span><span style="color: blue; font-weight: bold">def </span>depthFirstSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">):
</span><span style="color: darkred">"""
Search the deepest nodes in the search tree first.

Your search algorithm needs to return a list of actions that reaches the
Expand All @@ -108,32 +103,59 @@ def depthFirstSearch(problem):
print "Is the start a goal?", problem.isGoalState(problem.getStartState())
print "Start's successors:", problem.getSuccessors(problem.getStartState())
"""
# Problem with this code: does not use linear space
return generalPurposeSearch(problem, util.Stack())


def breadthFirstSearch(problem):
"""Search the shallowest nodes in the search tree first."""
return generalPurposeSearch(problem, util.Queue())
</span><span style="color: red">"*** YOUR CODE HERE ***"
</span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

</span><span style="color: blue; font-weight: bold">def </span>breadthFirstSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">):
</span><span style="color: darkred">"""Search the shallowest nodes in the search tree first."""
</span><span style="color: red">"*** YOUR CODE HERE ***"
</span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

def uniformCostSearch(problem):
"""Search the node of least total cost first."""
return generalPurposeSearch(
problem,
util.PriorityQueueWithFunction(lambda x: x[2]))

</span><span style="color: blue; font-weight: bold">def </span>uniformCostSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">):
</span><span style="color: darkred">"""Search the node of least total cost first."""
</span><span style="color: red">"*** YOUR CODE HERE ***"
</span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()

def aStarSearch(problem, heuristic=nullHeuristic):
"""Search the node that has the lowest combined cost and heuristic first."""
return generalPurposeSearch(
problem,
util.PriorityQueueWithFunction(lambda x: x[3]),
heuristic)


# Abbreviations
bfs = breadthFirstSearch
dfs = depthFirstSearch
astar = aStarSearch
ucs = uniformCostSearch
</span><span style="color: blue; font-weight: bold">def </span>nullHeuristic<span style="font-weight: bold">(</span>state<span style="font-weight: bold">, </span>problem<span style="font-weight: bold">=</span><span style="color: blue">None</span><span style="font-weight: bold">):
</span><span style="color: darkred">"""
A heuristic function estimates the cost from the current state to the nearest
goal in the provided SearchProblem. This heuristic is trivial.
"""
</span><span style="color: blue; font-weight: bold">return </span><span style="color: red">0

</span><span style="color: blue; font-weight: bold">def </span>aStarSearch<span style="font-weight: bold">(</span>problem<span style="font-weight: bold">, </span>heuristic<span style="font-weight: bold">=</span>nullHeuristic<span style="font-weight: bold">):
</span><span style="color: darkred">"""Search the node that has the lowest combined cost and heuristic first."""
</span><span style="color: red">"*** YOUR CODE HERE ***"
</span>util<span style="font-weight: bold">.</span>raiseNotDefined<span style="font-weight: bold">()


</span><span style="color: green; font-style: italic"># Abbreviations
</span>bfs <span style="font-weight: bold">= </span>breadthFirstSearch
dfs <span style="font-weight: bold">= </span>depthFirstSearch
astar <span style="font-weight: bold">= </span>aStarSearch
ucs <span style="font-weight: bold">= </span>uniformCostSearch

</pre>
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