Google Research Football environment follows GYM API design:
reset()- resets environment to the initial state.observation, reward, done, info = step(action)- performs a single step.observation = observation()- returns current observations.render(mode=human|rgb_array)- can be called at any time to enable rendering. The main difference from the GYM API is that callingrenderenables continuous rendering of the episode (no need to call the method on each step). Callingrenderenables pixels to be available in the observation. Note - rendering slows downstepmethod significantly.disable_render()- disables rendering previously enabled withrendercall.close()- releases environment object.
On top of the standard API, we provide a number of additional methods:
state = get_state()- provides a current environment's state containing all values affecting environment's behavior (random number generator state, current players' mental model, physics etc.). The state returned is an opaque object to be consumed byset_state(state)API method in order to restore environment's state from the past.set_state(state)- restores environment's state to previously snapshoted state usingget_state(). This method can be used to check outcome of executing sequences of different actions starting at a fixed state.write_dump(name)- writes a dump of the current scenario to the disk. Dump contains a snapshot of observations for each step of the episode and can be used to analyze episode's trajectory offline.
For example API usage have a look at play_game.py.