Asa H action selection

At any given time various layers of Asa H may predict 1 or more cases that will be active next.  Higher layers make their predictions based upon a longer span of inputs.  (And make a larger number of predictions that reach further into the future.) Some of these predicted cases can involve predicted actions Asa could perform. During the course of experimenting with several hundred Asa H programs I have tried out a number of different action selection algorithms.  With the entire Asa network acting as an evaluation function each of the possible actions can be "tried" (simulated) to see which gives the highest utility. No output action is actually taken during this simulation/evaluation stage.  The simulated action, actions, or non action which gives the highest utility (measured at the top of the network hierarchy) is then selected and is scheduled to be taken 1 or more time steps into the future. (Actions scheduled far enough into the future could subsequently be preempted by further future predictions and evaluations.) To reduce search/complexity one can put a time limit on how far into the future one looks and tries to predict (establish an "horizon").