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A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

Home Page: https://chuacheowhuan.github.io

License: MIT License

Python 3.93% Jupyter Notebook 96.07%
multi-agent-reinforcement-learning gym-environment limit-order-book high-frequency-trading ray rllib market-microstructure financial-engineering self-play double-auction

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gym-continuousdoubleauction's Issues

Agent_ids

Hi,
I am trying to run "CDA_NSP", but I get this error
"The element returned by reset() has agent_ids that are not the names of the agents in the env.
Agent_ids in this MultiAgentDict: [0, 1, 2, 3, 4, 5, 6, 7, 8]
Agent_ids in this env:[].
You likley need to add the private attribute _agent_ids to your env, which is a set containing the ids of agents supported by your env."

I am new to rllib, I do not know what to do to solve it.

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