
makeObservationModel(hallwayColors,
obsNoise)
Returns:
conditional distribution specifying probability of observing a color
given the robot's location 



perfectObsNoiseModel(actualColor)
Returns:
DDist over observed colors when in a room that has
actualColor . 



noisyObsNoiseModel(actualColor)
Returns:
DDist over observed colors when in a room that has
actualColor . 



makeTransitionModel(dynamics,
noiseDist,
hallwayLength)
Returns:
P(actualResultingLoc  previousLoc, action) represented as a function
that takes an action and returns a function that takes a previous
location and returns a distribution over actual resulting locations. 



standardDynamics(loc,
act,
hallwayLength)
Returns:
new loc of the robot assuming perfect execution. 



ringDynamics(loc,
act,
hallwayLength)
Returns:
new loc of the robot, assuming perfect execution where the hallway is
actually a ring (so that location 0 is next to location
hallwayLength 1 ). 



perfectTransNoiseModel(nominalLoc,
hallwayLength)
Returns:
distribution over resulting locations, modeling noisy execution of
commands; in this case, the robot goes to the nominal location with
probability 1.0 



noisyTransNoiseModel(nominalLoc,
hallwayLength)
Returns:
distribution over resulting locations, modeling noisy execution of
commands; in this case, the robot goes to the nominal location with
probability 0.8, goes one step too far left with probability 0.1, and
goes one step too far right with probability 0.1. 



leftSlipTransNoiseModel(nominalLoc,
hallwayLength)
Returns:
distribution over resulting locations, modeling noisy execution of
commands; in this case, the robot goes to the nominal location with
probability 0.9, and goes one step too far left with probability 0.1. 





wrapTextUI(m)
Returns:
A composite machine that prompts the user for input to, and prints
the output of m on each step. 



wrapWindowUI(m,
worldColors,
legalInputs,
windowName=' Belief ' ,
initBelief=None)
Returns:
A composite machine that prompts the user for input to, and
graphically displays the output of m on each step. 



drawBelief(belief,
window,
numStates,
drawNums=True) 



makeSESwithGUI(worldSM,
realColors,
legalInputs,
initBelief=None,
verbose=False,
title=' hallway ' )
Makes a colored hallway simulator and state estimator. 



makeSim(hallwayColors,
legalInputs,
obsNoise,
dynamics,
transNoise,
title=' sim ' ,
initialDist=None)
Make an instance of the simulator with noisy motion and sensing
models. 



hallSE(hallwayColors,
legalInputs,
obsNoise,
dynamics,
transNoise,
initialDist=None,
verbose=True) 

