enter reinforcement

reinforcement/environment.py

@@ -0,0 +1,56 @@
+# environment.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).
+
+
+#!/usr/bin/python
+
+class Environment:
+
+    def getCurrentState(self):
+        """
+        Returns the current state of enviornment
+        """
+        abstract
+
+    def getPossibleActions(self, state):
+        """
+          Returns possible actions the agent
+          can take in the given state. Can
+          return the empty list if we are in
+          a terminal state.
+        """
+        abstract
+
+    def doAction(self, action):
+        """
+          Performs the given action in the current
+          environment state and updates the enviornment.
+
+          Returns a (reward, nextState) pair
+        """
+        abstract
+
+    def reset(self):
+        """
+          Resets the current state to the start state
+        """
+        abstract
+
+    def isTerminal(self):
+        """
+          Has the enviornment entered a terminal
+          state? This means there are no successors
+        """
+        state = self.getCurrentState()
+        actions = self.getPossibleActions(state)
+        return len(actions) == 0