robcaulk
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b708134c1a
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switch multiproc thread count to rl_config definition
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2022-08-24 13:00:55 +02:00 |
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robcaulk
|
b26ed7dea4
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fix generic reward, add time duration to reward
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2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
280a1dc3f8
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add live rate, add trade duration
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2022-08-24 13:00:55 +02:00 |
|
robcaulk
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f9a49744e6
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add strategy to the freqai object
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2022-08-24 13:00:55 +02:00 |
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richardjozsa
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a2a4bc05db
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Fix the state profit calculation logic
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2022-08-24 13:00:55 +02:00 |
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robcaulk
|
29f0e01c4a
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expose environment reward parameters to the user config
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2022-08-24 13:00:55 +02:00 |
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robcaulk
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d88a0dbf82
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add sb3_contrib models to the available agents. include sb3_contrib in requirements.
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2022-08-24 13:00:55 +02:00 |
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robcaulk
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8b3a8234ac
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fix env bug, allow example strat to short
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2022-08-24 13:00:55 +02:00 |
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mrzdev
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8cd4daad0a
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Feat/freqai rl dev (#7)
* access trades through get_trades_proxy method to allow backtesting
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2022-08-24 13:00:55 +02:00 |
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robcaulk
|
3eb897c2f8
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reuse callback, allow user to acces all stable_baselines3 agents via config
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2022-08-24 13:00:55 +02:00 |
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robcaulk
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4b9499e321
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improve nomenclature and fix short exit bug
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2022-08-24 13:00:55 +02:00 |
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sonnhfit
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4baa36bdcf
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fix persist a single training environment for PPO
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2022-08-24 13:00:55 +02:00 |
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robcaulk
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f95602f6bd
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persist a single training environment.
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2022-08-24 13:00:55 +02:00 |
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robcaulk
|
5d4e5e69fe
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reinforce training with state info, reinforce prediction with state info, restructure config to accommodate all parameters from any user imported model type. Set 5Act to default env on TDQN. Clean example config.
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2022-08-24 13:00:55 +02:00 |
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sonnhfit
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7962a1439b
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remove keep low profit
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2022-08-24 13:00:55 +02:00 |
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sonnhfit
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81b5aa66e8
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make env keep current position when low profit
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2022-08-24 13:00:55 +02:00 |
|
sonnhfit
|
45218faeb0
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fix coding convention
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2022-08-24 13:00:55 +02:00 |
|
richardjozsa
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d55092ff17
|
Docker building update, and TDQN repair with the newer release of SB+
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2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
74e4fd0633
|
ensure config example can work with backtesting RL
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2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
b90da46b1b
|
improve price df handling to enable backtesting
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2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
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2080ff86ed
|
5ac base fixes in logic
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2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
16cec7dfbd
|
fix save/reload functionality for stablebaselines
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2022-08-24 13:00:55 +02:00 |
|
sonnhfit
|
0475b7cb18
|
remove unuse code and fix coding conventions
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
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d60a166fbf
|
multiproc TDQN with xtra callbacks
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2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
dd382dd370
|
add monitor to eval env so that multiproc can save best_model
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2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
69d542d3e2
|
match config and strats to upstream freqai
|
2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
e5df39e891
|
ensuring best_model is placed in ram and saved to disk and loaded from disk
|
2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
bf7ceba958
|
set cpu threads in config
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2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
57c488a6f1
|
learning_rate + multicpu changes
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2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
48bb51b458
|
example config added
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
b1fc5a06ca
|
example config added
|
2022-08-24 13:00:55 +02:00 |
|
sonnhfit
|
6d8e838a8f
|
update tensorboard dependency
|
2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
acf3484e88
|
add multiprocessing variant of ReinforcementLearningPPO
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2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
cf0731095f
|
type fix
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
1c81ec6016
|
3ac and 5ac example strategies
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
13cd18dc9a
|
PPO policy change + verbose=1
|
2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
926023935f
|
make base 3ac and base 5ac environments. TDQN defaults to 3AC.
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
096533bcb9
|
3ac to 5ac
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
718c9d0440
|
action fix
|
2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
9c78e6c26f
|
base PPO model only customizes reward for 3AC
|
2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
6048f60f13
|
get TDQN working with 5 action environment
|
2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
d4db5c3281
|
ensure TDQN class is properly named
|
2022-08-24 13:00:55 +02:00 |
|
robcaulk
|
91683e1dca
|
restructure RL so that user can customize environment
|
2022-08-24 13:00:55 +02:00 |
|
sonnhfit
|
ecd1f55abc
|
add rl module
|
2022-08-24 13:00:55 +02:00 |
|
sonnhfit
|
70b25461f0
|
add rl dependency
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
9b895500b3
|
initial commit - new dev branch
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
cd3fe44424
|
callback function and TDQN model added
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
01232e9a1f
|
callback function and TDQN model added
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
8eeaab2746
|
add reward function
|
2022-08-24 13:00:55 +02:00 |
|
MukavaValkku
|
ec813434f5
|
ReinforcementLearningModel
|
2022-08-24 13:00:55 +02:00 |
|