Add a characteristic for solvers using action masks and make use of it in rollout

[nhuet]

• Use it in rollout to make them be aware of current action mask, by calling their retrieve_applicable_actions() method.
• Add a get_action_mask() method to domains by default converting applicable actions space into a 0-1 numpy array, provided that the action space of each agent is an EnumerableSpace.
• Use these new features to simplify how the RayRLlib solver handles action masking:
  • inherit from Maskable
  • do not require anymore FullObservable from the domain to use action
    masking, as get_action_mask() can be called without the solver knowing about
    the current state (and since in rollout, the actual domain is now
    used)
  • decide whether using action masking directly in __init__() so that
    using_applicable_actions() can be overriden properly
  • use common functions for unwrap_obs and wrap_action in solver and
    wrapper environment to avoid code duplication
  • use domain.get_action_mask() to convert applicable actions into a mask
    (the method is more efficient as not calling get_applicable_actions()
    for each actions)