Data Science, Reinforcement Learning, Q Learning, S P 500 Index, Finance.
find_action(policy, current_value): if policy.loc[current_value, :].sum().sum() == 0: return random.choice(['buy_buy', 'buy_sell', 'sell_sell', 'sell_buy']) return policy.columns[np.argmax(policy.loc[current_value, :].values)] def update_policy(reward, current_state_value, action): LEARNING_RATE =