text: In the following, we proceed to describe the generative model used by the agent, 
  which here was identically structured to the generative process, the actual environmental 
  process generating the data. In the maze task, the environmental states and concurrent 
  observations were multidimensional, while the actions were unidimensional. Here, we refer 
  to the different dimensions of the environment as state factors and the different dimensions 
  of the observations as observation modalities. There were two state factors, the location of the 
  agent and the reward condition: 
  
  **State Factor 1 (Location):** **State Factor 2 (Reward Condition):**
  
  1. 
  2. 
  3. 
  4.  Centre location; 
  Right arm; 
  Left arm; 
  Cue location. 
  
  1. 
  2.  Reward condition right; 
  Reward condition left. 
  
  The first factor described which of the four locations in the maze the agent was 
  inhabiting—the centre, cue location, and left and right arms—and was controlled by the 
  action. The second factor was the reward condition factor, and had two possible states: the 
  reward location being on the right or on the left. The agent’s actions directly controlled the 
  first factor, while it had to infer the second based on the cue in order to complete the task. 
  There were three observation modalities: one for observing the agent’s own location, one 
  for observing rewards and one for observing the cue: 