Single Comment

| Pruning techniques are commonly based on calculated values of the 
| piece movements. But what if these values are 'outside' the movement?

It seems your thinking is badly influenced by Zillions, which indeed seems to derive values of the pieces from their mobilities. It must, because it does not have any prior knowledge of the value of the pieces. When I write a dedicated program for a certain game, though, I measure the value of the involved pieces through asymmetric play-testing, and then program these values in 'by hand'. 

| For example: The Drone would be calculated at an extremely low value 
| since its immediate movement does not result in the loss of material 
| for the opponent. But it has another value which does not present 
| itself until later in the game. Without a Drone, a player cannot 
| promote a Highborn and thus risks losing the production phase of the 
| turn.

If having an extra Drone is as good as having 5 extra Soldiers, for whatever reason, the play-testing will reveal that. And I would simply award that score for the Drone being on the board, even if a Drone were a piece thas no moves at all.

These are not properties that make a game difficult for a computer to play. It might be difficult to acquire the knowledge that need to go in such a program, and it is unlikely that the program will be able to derive deep strategic motives in a few seconds with no other information than the rules. It takes thousands of high-quality Capablanca Chess games to derive a value for Archbishop and Chancellor. But it is not realistic to require that a program has to discover that knowledge for itself within a single game. If we teach people how to play Chess, we do tell them the piece values, even though they are not part of the rules at all.