--- title: RecSys RL Env keywords: fastai sidebar: home_sidebar summary: "OpenAI Gym's Box environment that simulates a recommendation system by picking item and giving feedback signals." description: "OpenAI Gym's Box environment that simulates a recommendation system by picking item and giving feedback signals." nb_path: "nbs/rl/envs/recsys.ipynb" ---
class Config(object):
action_size = 1
state_size = 6
env_n_components = 32
saves_folder_path = './'
env_tol = 1e-4
env_max_iter = 1000
env_alpha = 0.001
total_group_num = 3
history_length = 2
rewards = [0, 1]
config = Config()
from scipy.sparse import coo_matrix
group_ids = np.array([1,1,1,2,2,3])
item_ids = np.array([1,2,3,2,3,1])
ratings = np.array([1,0,0,1,1,0])
rating_matrix = coo_matrix((ratings, (group_ids, item_ids)), shape=(4, 4)).tocsr()
env = Env(config=config, rating_matrix=rating_matrix, dataset_name='val')
state = env.reset()
state
new_state, reward, _, _ = env.step(0)
new_state, reward