**How severe does this issue affect your experience of using Ray?**

- High: It blocks me to complete my task.

Hi, I have been reading several tutorials (see belo) and I am not sure what is required on the **init**, and what can be left for the 'step()'method.

I am creating my won environment I have 50 (or more) agents in total.They form 2 groups:

- 1 agent is only the “proposer”, with some convoluted
**action**space that looks like this: ([1,0,0][0.25,0.5, 025]) - The other 49 are the “responders” with
**action**space just 1 or 0.

**Question: I am trying to understand what needs to be defined on the** **init****and what can be left for the step method.**

In particular, since I have 49 (or more) responders, I wonder where I need to map them to their action and observation spaces.

**option a)** Should I create 49 responder-agents entries on the dict defined in the init method.

- a dictionary of 50 agents IDs
- a dictionary with
**50 entries**like this:**Something like (very inelegant):**

`

self.action_space = gym.spaces.Dict( {

‘proposer’: gym.spaces.Tuple((gym.spaces.MultiBinary(self.n_agents), gym.spaces.Box(low=0.0, high=1.0,shape=(self.n_agents,)))),

‘responder1’: Discrete(2)

‘responder2’: Discrete(2)

…etc

} )

`

**option b)** Define the init in a more abstract way:

- a dictionary of 50 agents IDs
- a dictionary with only 2 entries (instead of 50):

self.action_space = gym.spaces.Dict( {

‘proposer’: gym.spaces.Tuple((gym.spaces.MultiBinary(self.n_agents), gym.spaces.Box(low=0.0, high=1.0,shape=(self.n_agents,)))),

‘responder’: Discrete(2)

})

and then… under this option, on the **step** method, I will say: “here are the ID’s of 49 agents, map their action to the “responder” in the dictionary (with only 2 entries) I gave you on the init.

NB:

I have already read these tutorials and examples and I am not clear:

self play with open spiel

This one only shows option (a), but seems to suggest that option (b) is possible

multi-agent-and-hierarchical

This one only shows option (a) but it’s for only 2 agents:

multi_agent_different_spaces_for_agents.py

Thanks!