In my earlier post I was considering combining game theory and measure theory methodologies of MAS and swarm systems.  From my research into this topic I found this paper https://jacobstechnology.com/acs/pdf/ESOA06Hybrid.pdf.  Although it seems like the people who published it are respectable, the paper has never been cited.  Which is strange since it is an interesting topic.  They came to the same questions I have about combining agent/swarm methodologies.

To what extent can we construct a unified development methodology that supports
both extremes (and thus intermediate agent types as well)? It is clumsy to have to use
one methodology [38] for BDI agents, and a completely separate one [26] for
swarming agents. Hybrid systems will only become commonplace when both kinds of
agents can be developed within an integrated framework.

They believe that integrating different agent models is an important problem.

Also, before that paper was published, GMU had published a paper Cooperative Multiagent Learning: The State of the Art.  In their conclusion they stated the need for Team Heterogeneity.  Meaning that the team is composed of agents with differing abilities.  They also make the case for when the team is too large that the agent’s abilities can’t all be different.  This is the conclusion I came to.  For example, when there are swarms interacting with more complex multiagent systems.  How do they cooperate and learn from each other?  What is the framework for such interaction?  How can the agent’s mathematical underpinnings act as a catalyst for communication for teaching/learning?  Can a universal framework be developed?