def depthFirstSearch(problem):
"""
Search the deepest nodes in the search tree first [p 85].
Your search algorithm needs to return a list of actions that reaches
the goal. Make sure to implement a graph search algorithm [Fig. 3.7].
To get started, you might want to try some of these simple commands to
understand the search problem that is being passed in:
print "Start:", problem.getStartState()
print "Is the start a goal?", problem.isGoalState(problem.getStartState())
print "Start's successors:", problem.getSuccessors(problem.getStartState())
"""
"*** YOUR CODE HERE ***"
f = open('maze.P', 'r')
for line in f:
if "goal" in line:
g = line
last = line
print "lastline", last
print "goal", g
f.close()
refine = last.split("(")
refine2 = refine[1].split(")")
startPac = refine2[0]
myXSB = pyxf.xsb("/home/nikhil/Downloads/XSB/bin/xsb")
myXSB.load("maze.P")
myXSB.load("dfs.P")
result = myXSB.query("depthFirstSearch(" + startPac + ", Path,Direction).")
print result
x = result[0]['Path']
f1 = x.split("[")
neededDir = f1[1].split(",")
gg = g.split("(")
g2 = gg[1].split(")")
ls = []
f2 = open('maze.P', 'r')
for i in xrange(len(neededDir)):
f2 = open('maze.P', 'r')
for line1 in f2:
if i + 1 < len(neededDir):
stri = neededDir[i] + "," + neededDir[i + 1]
if i + 1 < len(neededDir) and stri in line1:
j = line1.split(",")
k = j[2].split(").")
print line1, neededDir[i], neededDir[i + 1], k[0]
if g2[0] == neededDir[i + 1]:
exit
ls.append(str(k[0]))
continue
f2.close()
return ls
"""for x in xrange(len(array)):
def aStarSearch(problem, heuristic=nullHeuristic):
"Search the node that has the lowest combined cost and heuristic first."
"*** YOUR CODE HERE ***"
f = open('maze.P','r')
for line in f:
pass
last = line
refine = last.split("(")
refine2 = refine[1].split(")")
startPac = refine2[0]
myXSB = pyxf.xsb("/home/nikhil/Downloads/XSB/bin/xsb")
myXSB.load("maze.P")
myXSB.load("AStar.P")
result = myXSB.query("AStarAlgorithm("+startPac+",Path,Direction).")
print result
def aStarSearch(problem, heuristic=nullHeuristic):
"Search the node that has the lowest combined cost and heuristic first."
"*** YOUR CODE HERE ***"
f = open('maze.P', 'r')
for line in f:
pass
last = line
refine = last.split("(")
refine2 = refine[1].split(")")
startPac = refine2[0]
myXSB = pyxf.xsb("/home/nikhil/Downloads/XSB/bin/xsb")
myXSB.load("maze.P")
myXSB.load("AStar.P")
result = myXSB.query("AStarAlgorithm(" + startPac + ",Path,Direction).")
print result
def breadthFirstSearch(problem):
"Search the shallowest nodes in the search tree first. [p 81]"
"*** YOUR CODE HERE ***"
f = open('maze.P','r')
for line in f:
pass
last = line
refine = last.split("(")
refine2 = refine[1].split(")")
startPac = refine2[0]
myXSB = pyxf.xsb("/home/nikhil/Downloads/XSB/bin/xsb")
myXSB.load("maze.P")
myXSB.load("bfs.P")
if sys.argv=="CornersProblem":
myXSB = pyxf.xsb("/home/nikhil/Downloads/XSB/bin/xsb")
myXSB.load("maze.P")
myXSB.load("CornersProblem.P")
result = myXSB.query("breadthFirstSearch("+startPac+",Path,Direction).")
print result
else:
result = myXSB.query("breadthFirstSearch("+startPac+",Path,Direction).")
print result
def breadthFirstSearch(problem):
"Search the shallowest nodes in the search tree first. [p 81]"
"*** YOUR CODE HERE ***"
f = open('maze.P', 'r')
for line in f:
pass
last = line
refine = last.split("(")
refine2 = refine[1].split(")")
startPac = refine2[0]
myXSB = pyxf.xsb("/home/nikhil/Downloads/XSB/bin/xsb")
myXSB.load("maze.P")
myXSB.load("bfs.P")
if sys.argv == "CornersProblem":
myXSB = pyxf.xsb("/home/nikhil/Downloads/XSB/bin/xsb")
myXSB.load("maze.P")
myXSB.load("CornersProblem.P")
result = myXSB.query("breadthFirstSearch(" + startPac +
",Path,Direction).")
print result
else:
result = myXSB.query("breadthFirstSearch(" + startPac +
",Path,Direction).")
print result
def depthFirstSearch(problem):
"""
Search the deepest nodes in the search tree first [p 85].
Your search algorithm needs to return a list of actions that reaches
the goal. Make sure to implement a graph search algorithm [Fig. 3.7].
To get started, you might want to try some of these simple commands to
understand the search problem that is being passed in:
print "Start:", problem.getStartState()
print "Is the start a goal?", problem.isGoalState(problem.getStartState())
print "Start's successors:", problem.getSuccessors(problem.getStartState())
"""
"*** YOUR CODE HERE ***"
f = open('maze.P','r')
for line in f:
if "goal" in line:
g = line
last = line
print "lastline",last
print "goal",g
f.close()
refine = last.split("(")
refine2 = refine[1].split(")")
startPac = refine2[0]
myXSB = pyxf.xsb("/home/nikhil/Downloads/XSB/bin/xsb")
myXSB.load("maze.P")
myXSB.load("dfs.P")
result = myXSB.query("depthFirstSearch("+startPac+", Path,Direction).")
print result
x = result[0]['Path']
f1 = x.split("[")
neededDir = f1[1].split(",")
gg = g.split("(")
g2 = gg[1].split(")")
ls = []
f2 = open('maze.P','r')
for i in xrange(len(neededDir)):
f2 = open('maze.P','r')
for line1 in f2:
if i+1<len(neededDir):
stri = neededDir[i] + "," + neededDir[i+1]
if i+1<len(neededDir) and stri in line1:
j = line1.split(",")
k = j[2].split(").")
print line1,neededDir[i],neededDir[i+1],k[0]
if g2[0]==neededDir[i+1]:
exit
ls.append(str(k[0]))
continue
f2.close()
return ls
"""for x in xrange(len(array)):
