Hello, I have a multiagent environment on which 2 agents bargain. It is like a"turn-based" environment. Similar to this: e.g. user1 action → env obs for user2 → user2 action → env obs for user1 → user1 action, etc… In particular: In one round, an agent propose a price for an asset, say $50.87 a…

Hey @Username1 , Exactly. I am not 100% sure what does self._spaces_in_preferred_format = True does, but I found the following comment in the docs: # Do the action and observation spaces map from agent ids to spaces # for the individual agents? So my guess would be that when this is True you ex…

Hi @Username1 , Welcome to the forum. Perhaps this post may be a helpful place to start. [image] Multi-agent: Where does the "first structure" comes from? RLlib How severe does this issue affect your experience of using Ray? Medium: It contributes to significant diffic…

Hello @mannyv , thank you very much for this pointer. I have some questions to clarify. My setting is as follows: Similar to a “turn-based game” .I have 50 agents. On each round, one agent is picked at random and makes a move. The other agents 49 agents observe the move and each respond with a bina…

Hi @Username1 , Beside @mannyv ’s pointer, I would recommend looking into RLlib examples at GitHub: multi_agent_different_spaces_for_agents.py self_play_with_open_spiel.py is linked at docs as an example for turn-based games I guess combining the two above should give you the answer. I would rec…

Hello @vlainic , thank you very much for these examples. They are indeed very useful. My undestanding is that: a) yes, every agent should have an ID defined at the init Then at every turn, on the “step” method, one should map the available actions/ observations class to each ID. what is this meth…

yes! thank you very much. I am confused between using “discrete(number of agents)” or: “multibinary” So something like this: gym.spaces.Tuple( (gym.spaces.MultiBinary(number of agents), gym.spaces.Box(low=0.0, high=1.0,shape=(number of agents,))) ) To put an example, the “proposer” will prop…

Well, it’s kind of off-topic what you ask now, and I do not know your application/problem. I advise looking into gym github for what does each space type does. Each py-file has a clear example at the class explanation :wink:

Thank you very much for this example and your answers. Thanks so much!

Mutiagent - Different action space for different agents

RLlib

mannyv August 23, 2022, 3:22pm 2

Hi @Username1,

Welcome to the forum.

Perhaps this post may be a helpful place to start.

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Initialization of multiagent envs RLlib	8	542	August 31, 2022
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Obervation space and action space in multi-agent env RLlib	3	442	August 14, 2021
Different observation space in MultiAgentEnv RLlib	2	807	August 12, 2021
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Mutiagent - Different action space for different agents

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