I think that's basically what their algorithm does:
> We use an evolutionary algorithm to evolve sequences of actions that could make up a single turn. The fitness function is the quality of the board state of the end of the turn, as measured by some straightforward metrics.
My interpretation of this (and your suggestion) is that they take the number of possible actions in one turn, and prune them according to how they affect the board state. That seems to be what you're describing.
Evaluating those pruned action sets across multiple turns seems like the next logical state.
They claim the pruned branches based on potential actions is a novel approach, but it seems common sense to me and I'd be surprised that several other games aren't already implementing this in some fashion.
> We use an evolutionary algorithm to evolve sequences of actions that could make up a single turn. The fitness function is the quality of the board state of the end of the turn, as measured by some straightforward metrics.
My interpretation of this (and your suggestion) is that they take the number of possible actions in one turn, and prune them according to how they affect the board state. That seems to be what you're describing.
Evaluating those pruned action sets across multiple turns seems like the next logical state.