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# 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
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