policies.py

from pd_main import *
import random

# # random policy #
# def PRandom(possible_actions):
#   return random.choice(possible_actions)
#
# # exploit policy #
# def PExploit(possible_actions, agent, row, col):
#   duplicate = []
#
#   q_table = dropoff_q_table if agent.hasBlock() else pickup_q_table
#
#   # choose action with best q-value 80% of the time
#   if random.random() <= 0.8:
#     max_action = possible_actions[0]
#     for num in possible_actions:
#       q_value = q_table[row][col][num]
#       max_q_value = q_table[row][col][max_action]
#
#       if q_value > max_q_value:
#         max_action = num
#         duplicate.clear()
#         duplicate.append(num)
#       if q_value == max_q_value:
#         duplicate.append(num)
#
#     exploit_choice = random.choice(duplicate) if len(duplicate) > 1 else max_action
#   else:
#     exploit_choice = random.choice(possible_actions)
#
#   return exploit_choice
#
# # greedy policy #
# def PGreedy(possible_actions, agent, row, col):
#   duplicate = []
#
#   q_table = dropoff_q_table if agent.hasBlock() else pickup_q_table
#
#   # choose action with best q-value 100% of the time
#   max_action = possible_actions[0]
#   for num in possible_actions:
#     q_value = q_table[row][col][num]
#     max_q_value = q_table[row][col][max_action]
#
#     if q_value > max_q_value:
#       max_action = num
#       duplicate.clear()
#       duplicate.append(num)
#     if q_value == max_q_value:
#       duplicate.append(num)
#
#   greedy_choice = random.choice(duplicate) if len(duplicate) > 1 else max_action
#
#   return greedy_choice