| """ | |
| RL BTC v4 — Offline Implicit Q-Learning for Bitcoin Trading. | |
| Based on: "Offline Reinforcement Learning with Implicit Q-Learning" (Kostrikov et al., 2021) | |
| https://hf.co/papers/2110.06169 | |
| Key innovation: learns from logged historical data without environment interaction. | |
| Uses upper expectile value function to estimate the value of the best actions | |
| without ever explicitly querying out-of-distribution actions. | |
| """ | |
| from .constants import ( | |
| DEFAULT_DATA_PATH, | |
| MARKET_FEATURE_COLUMNS, | |
| PORTFOLIO_FEATURE_COLUMNS, | |
| ACTIONS, | |
| N_ACTIONS, | |
| ACTION_INDEX_BY_NAME, | |
| STARTING_CASH, | |
| DRAWDOWN_LIMIT, | |
| ) | |
| from .env import BTCTradingEnv | |
| from .dataset import build_offline_rl_dataset, OfflineRLDataset | |
| from .iql_trainer import IQLTrainer, IQLConfig | |