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fix PER sign issue #108

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merged 6 commits into from
Apr 4, 2017
Merged

fix PER sign issue #108

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bf599ab
correct doubleboltzmannpolicy for PER
kengz Apr 4, 2017
b3d8fe7
reschedule mountain per
kengz Apr 4, 2017
3dbd0eb
schedule mountain per
kengz Apr 4, 2017
13b58a3
reschedule mountain per, has hope!
kengz Apr 4, 2017
fa70057
fix negative rewards bug by adding bump to all
kengz Apr 4, 2017
1d707e7
reschedule lunar and acrobot per
kengz Apr 4, 2017
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11 changes: 6 additions & 5 deletions rl/memory/prioritized_exp_replay.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,15 +27,16 @@ def __init__(self, env_spec, max_mem_len=10000, e=0.01, alpha=0.6,
self.prio_tree = SumTree(self.max_mem_len)
self.head = 0

# bump to account for negative terms in reward get_priority
# and we cannot abs(reward) cuz it's sign sensitive
SOLVED_MEAN_REWARD = self.env_spec['problem']['SOLVED_MEAN_REWARD']
if SOLVED_MEAN_REWARD > 0:
self.min_priority = 0
else:
self.min_priority = abs(10 * SOLVED_MEAN_REWARD)
self.min_priority = abs(10 * SOLVED_MEAN_REWARD)

def get_priority(self, error):
# add min_priority to prevent root of negative = complex
return (self.min_priority + error + self.e) ** self.alpha
p = (self.min_priority + error + self.e) ** self.alpha
assert not np.isnan(p)
return p

def add_exp(self, action, reward, next_state, terminal):
'''Round robin memory updating'''
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6 changes: 3 additions & 3 deletions rl/spec/box2d_experiment_specs.json
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Expand Up @@ -106,15 +106,15 @@
"Policy": "DoubleDQNBoltzmannPolicy",
"PreProcessor": "StackStates",
"param": {
"train_per_n_new_exp": 5,
"batch_size": 32,
"train_per_n_new_exp": 2,
"lr": 0.005,
"gamma": 0.99,
"hidden_layers": [800, 400],
"hidden_layers_activation": "sigmoid",
"output_layer_activation": "linear",
"exploration_anneal_episodes": 150,
"epi_change_lr": 200
"epi_change_lr": 200,
"max_mem_len": 30000
},
"param_range": {
"lr": [0.001, 0.005, 0.01],
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16 changes: 9 additions & 7 deletions rl/spec/classic_experiment_specs.json
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Expand Up @@ -94,7 +94,7 @@
"HyperOptimizer": "GridSearch",
"Memory": "PrioritizedExperienceReplay",
"Optimizer": "AdamOptimizer",
"Policy": "BoltzmannPolicy",
"Policy": "DoubleDQNBoltzmannPolicy",
"PreProcessor": "NoPreProcessor",
"param": {
"lr": 0.02,
Expand Down Expand Up @@ -460,7 +460,7 @@
"Policy": "DoubleDQNBoltzmannPolicy",
"PreProcessor": "StackStates",
"param": {
"train_per_n_new_exp": 4,
"train_per_n_new_exp": 1,
"lr": 0.01,
"gamma": 0.99,
"hidden_layers": [32],
Expand Down Expand Up @@ -667,23 +667,25 @@
"HyperOptimizer": "GridSearch",
"Memory": "PrioritizedExperienceReplay",
"Optimizer": "AdamOptimizer",
"Policy": "BoltzmannPolicy",
"Policy": "DoubleDQNBoltzmannPolicy",
"PreProcessor": "NoPreProcessor",
"param": {
"train_per_n_new_exp": 5,
"batch_size": 32,
"lr": 0.001,
"gamma": 0.99,
"hidden_layers": [128, 64],
"hidden_layers_activation": "sigmoid",
"output_layer_activation": "linear",
"exploration_anneal_episodes": 400,
"epi_change_lr": 600
"exploration_anneal_episodes": 200,
"epi_change_lr": 500,
"max_mem_len": 20000
},
"param_range": {
"lr": [0.001, 0.01],
"lr": [0.01, 0.02, 0.03, 0.05],
"gamma": [0.99, 0.999],
"hidden_layers": [
[400],
[800],
[400, 200]
]
}
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2 changes: 1 addition & 1 deletion rl/spec/problems.json
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@
"RENDER": true,
"GYM_ENV_NAME": "MountainCar-v0",
"SOLVED_MEAN_REWARD": -110.0,
"MAX_EPISODES": 2000,
"MAX_EPISODES": 1000,
"REWARD_MEAN_LEN": 100
},
"MountainCarContinuous-v0": {
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