def __init__(self, cmp, rewardSet, initialPhi, queryType, gamma, qi=False):
"""
qi: query iteration
"""
QTPAgent.__init__(self, cmp, rewardSet, initialPhi, queryType, gamma)
# do query iteration?
self.qi = qi
self.m = 1
if hasattr(self, 'computePiValue'):
# policy gradient agent has different ways to compute values..
self.computeV = lambda pi, S, A, r, horizon: self.computePiValue(pi, r, horizon)
else:
self.computeV = lambda pi, S, A, r, horizon: lp.computeValue(pi, r, S, A)
def __init__(self, mdp, k):
"""
qi: query iteration
"""
self.mdp = mdp
self.k = k
if hasattr(self, 'computePiValue'):
# policy gradient agent has different ways to compute values..
self.computeV = lambda pi, S, A, r, horizon: self.computePiValue(
pi, r, horizon)
else:
self.computeV = lambda pi, S, A, r, horizon: lp.computeValue(
pi, r, S, A)
def __init__(self, cmp, rewardSet, initialPhi, queryType, gamma, qi=False):
"""
qi: query iteration
"""
QTPAgent.__init__(self, cmp, rewardSet, initialPhi, queryType, gamma)
# do query iteration?
self.qi = qi
self.m = 1
if hasattr(self, 'computePiValue'):
# policy gradient agent has different ways to compute values..
self.computeV = lambda pi, S, A, r, horizon: self.computePiValue(
pi, r, horizon)
else:
self.computeV = lambda pi, S, A, r, horizon: lp.computeValue(
pi, r, S, A)
def computeValue(self, x): return computeValue(x, self.mdp.r, self.mdp.S, self.mdp.A)
def computeValue(self, x):
"""
compute the value of policy x. it computes the dot product between x and r
"""
return computeValue(x, self.mdp.r, self.mdp.S, self.mdp.A)
def computeValue(self, x):
return computeValue(x, self.mdp.r, self.mdp.S, self.mdp.A)