scRL.EnvironmentCore.deepEnv

class scRL.EnvironmentCore.deepEnv(gres, X_pca, max_step=50, KNN=100, reward_type='c', reward_mode='Decision', starts_probs=True)

Environment for deep reinforcement learning on grid embedding.

Parameters:

• gres – Grids results after reward generating.

• X_pca – The input latent space.

• max_step – Maximum steps the agent can travel in the environment. (Default: 50)

• KNN – Nearest neighbors for considering each grid points state value. (Default: 10)

• reward_type – The reward type generated. (Default: ‘c’) Two types are included:’c’,’d’.

• reward_mode – The reward mode selected when generating the reward. (Default: ‘Decision’) Two modes are included:’Decision’,’Contribution’.

__init__(gres, X_pca, max_step=50, KNN=100, reward_type='c', reward_mode='Decision', starts_probs=True)

Methods

__init__(gres, X_pca[, max_step, KNN, ...])
reset()
step(action)