Adaptive AI Engine for RTS Games

Discussing the theory and practice

On-line Planning for Resource Production in Real-Time Strategy Games -part5

Posted by ferasferas on November 5, 2010

Heuristic Scheduler

The previous component(sequential planner) finds a sequential plan. However, to accurately estimate the utility of any renewable resources, we need to reschedule actions to allow concurrency and decrease the makespan of the found plan. We do this by using a heuristic scheduling procedure that traverses the found action sequence in order. For each action Ai , the procedure moves the start time of Ai to the earliest possible time such that its preconditions are still satisfied.

Assume that Ai starts at time ts , and the state R+ (ts ) is the resource state at time ts after the effects of all actions that end at time ts are added to the game state, and R− (ts ) is the resource game state before the effects are added.

Obviously, the preconditions of Ai are satisfied by R+ (ts ). If they are also satisfied by R− (ts ), this means the satisfaction of the preconditions of Ai is not due to any of the actions that end at time ts , Then we can now move action Ai to start earlier than ts , to the previous decision epoch (time where an action starts or ends).This is repeated until the preconditions of A are satisfied by some R+ (ts ) but not R− (ts ), i.e., the satisfaction of the preconditions of A is due to the actions that end at time ts .

The plan is now rescheduled such that action A starts at time ts , and we can proceed to attempt to reschedule the next action in our sequential plan. The pseudo-code for this procedure is given in Algorithm 3.

We can show this procedure is sound using the following informal argument. We need to ensure that when we reschedule an action, every action between the new start time and the old start time remains executable.

Now when processing each action, we can always schedule it before a previous action if they do not consume or borrow the same resource:

1- Consider a pair of actions A and B, A before B, in a valid plan that both consume or borrow resource R, and assume we are about to reschedule B. First, if A and B are adjacent, the state before A must have enough R for A and B to execute. This means that at that state, A and B could be executed concurrently, or B could be scheduled before A, if possible.

2- On the other hand, if A and B were separated by any actions that produced R in order to satisfy B’s precondition, then our procedure would not shift B before the effects of those actions. If A and B are separated by actions not producing R, this effectively reduces to the adjacent case. Thus, this procedure is sound.

Future Work

While this procedure is not guaranteed to produce a plan with the optimal makespan, it is fast (at most quadratic in the number of actions) and performs well in practice. Investigating more complex scheduling algorithms for this problem is a topic of future work.


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