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Change min to max on the explanation of the halo's radial profile fun… #544

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Change min to max on the explanation of the halo's radial profile fun… #544

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Change min to max on the explanation of the halo's radial profile fun…
jomavera Jun 8, 2022
b4bd0c7
Add epsilon-greedy stategy in Chapter 6
jomavera Jun 9, 2022
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32 changes: 16 additions & 16 deletions Chapter5_LossFunctions/Ch5_LossFunctions_PyMC2.ipynb
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30 changes: 15 additions & 15 deletions Chapter5_LossFunctions/Ch5_LossFunctions_PyMC3.ipynb
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1,596 changes: 798 additions & 798 deletions Chapter5_LossFunctions/Ch5_LossFunctions_TFP.ipynb
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15 changes: 10 additions & 5 deletions Chapter6_Priorities/other_strats.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
#other strats.
# TODO: UBC strat, epsilon-greedy
# TODO: UBC strat

import scipy.stats as stats
import numpy as np
Expand Down Expand Up @@ -28,7 +28,7 @@ class GeneralBanditStrat(object):

"""

def __init__(self, bandits, choice_function):
def __init__(self, bandits, choice_function, epsilon=0.1):

self.bandits = bandits
n_bandits = len(self.bandits)
Expand All @@ -38,6 +38,7 @@ def __init__(self, bandits, choice_function):
self.choices = []
self.score = []
self.choice_function = choice_function
self.epsilon = epsilon

def sample_bandits(self, n=1):

Expand Down Expand Up @@ -97,9 +98,13 @@ def ucb_bayes(self):
return np.argmax(beta.ppf(alpha,
1 + self.wins,
1 + self.trials - self.wins))




def epsilon_greedy(self):
prob = np.random.random()
if prob <= self.epsilon:
return np.random.randint(0, len(self.wins))
else:
return np.argmax(self.wins / (self.trials +1))

class Bandits(object):
"""
Expand Down