Multi-task reinforcement learning with different action spaces

I'm currently working on a project in which I need apply multi -task reinforcement learning. Over the same state space, each agent aims to do a separate task, but the action spaces of agents are different from each other. I thought IMPALA would be a good choice at first glance, but it requires actions to be shared somehow, which is not applicable in my case.

Can someone please give me an idea if there is an appropriate multi-task reinforcement learning algorithm having more flexibility in choosing action spaces with references?