Add project 5 sources.

p5_classification/classificationAgents.py

@@ -0,0 +1,75 @@
+# classificationAgents.py
+# -----------------------
+# Licensing Information:  You are free to use or extend these projects for
+# educational purposes provided that (1) you do not distribute or publish
+# solutions, (2) you retain this notice, and (3) you provide clear
+# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.
+# 
+# Attribution Information: The Pacman AI projects were developed at UC Berkeley.
+# The core projects and autograders were primarily created by John DeNero
+# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
+# Student side autograding was added by Brad Miller, Nick Hay, and
+# Pieter Abbeel (pabbeel@cs.berkeley.edu).
+
+
+# pacmanAgents.py
+# ---------------
+# Licensing Information:  You are free to use or extend these projects for 
+# educational purposes provided that (1) you do not distribute or publish 
+# solutions, (2) you retain this notice, and (3) you provide clear 
+# attribution to UC Berkeley, including a link to 
+# http://inst.eecs.berkeley.edu/~cs188/pacman/pacman.html
+# 
+# Attribution Information: The Pacman AI projects were developed at UC Berkeley.
+# The core projects and autograders were primarily created by John DeNero 
+# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
+# Student side autograding was added by Brad Miller, Nick Hay, and 
+# Pieter Abbeel (pabbeel@cs.berkeley.edu).
+
+
+from pacman import Directions
+from game import Agent
+
+import random
+import game
+import util
+
+class DummyOptions:
+    def __init__(self):
+        self.data = "pacman"
+        self.training = 25000
+        self.test = 100
+        self.odds = False
+        self.weights = False
+
+
+import perceptron_pacman
+
+class ClassifierAgent(Agent):
+    def __init__(self, trainingData=None, validationData=None, classifierType="perceptron", agentToClone=None, numTraining=3):
+        from dataClassifier import runClassifier, enhancedFeatureExtractorPacman
+        legalLabels = ['Stop', 'West', 'East', 'North', 'South']
+        if(classifierType == "perceptron"):
+            classifier = perceptron_pacman.PerceptronClassifierPacman(legalLabels,numTraining)
+        self.classifier = classifier
+        self.featureFunction = enhancedFeatureExtractorPacman
+        args = {'featureFunction': self.featureFunction,
+                'classifier':self.classifier,
+                'printImage':None,
+                'trainingData':trainingData,
+                'validationData':validationData,
+                'agentToClone': agentToClone,
+        }
+        options = DummyOptions()
+        options.classifier = classifierType
+        runClassifier(args, options)
+    def getAction(self, state):
+        from dataClassifier import runClassifier, enhancedFeatureExtractorPacman
+        features = self.featureFunction(state)
+        
+        action =  self.classifier.classify([features])[0]
+
+        return action
+
+def scoreEvaluation(state):
+    return state.getScore()