Missing “Mask” Attribute when Training Multi-Agent PPO with RNN (LSTM) – Error in local_ppo_rnn_ (R2024b)

I am encountering a reproducible error when training a multi-agent reinforcement-learning environment with PPO and recurrent networks (LSTM) in MATLAB R2024b. Single-agent training with the same actor/critic and same Simulink environment runs without issues; the problem appears only in multi-agent training.

• During execution of local_ppo_rnn_, the trajectories mini-batch passed to the function lacks the Mask field (mb.Mask).
• In single-agent runs, padSequences correctly adds Mask, so the same code path works.
• In multi-agent runs, padSequences appears not to be invoked (or its result is not propagated), leading to the missing field and the runtime error.
• HasRecurrent is correctly detected as true (checked via rl.util.rlModelDescriptor).
• No custom ProcessExperienceFcn is used.

So, My questions are

1. Is this a known issue (bug) in R2024b for multi-agent RNN training?
2. Is there an official patch or workaround—other than disabling the recurrent layers or training agents individually?
3. If the fix is scheduled for a future release, could you provide an estimated timeline or a temporary code change (e.g., ensuring Mask gets added) that we can apply locally?

Thank you for your assistance.

[Haelee]

Hi, 홍렬. Could you kindly provide a code snippet that reproduces the issue, so that others can easily identify it?

Also, you can refer to the known bug/issue list from: External Bug Report - R2024b (Reinforcement Learning Toolbox)