To get that from the scent-following, hill-climbing algorithm requires some work.
To get that from the scent-following, hill-climbing algorithm requires some work.
The specific case you mention is discussed in the paper on page 6 - http://www.cs.colorado.edu/~ralex/papers/PDF/OOPSLA06antiobj... It's well-written and makes for an interesting read. As someone interested in AI but without much skill I found this approach much more intuitive, though I wonder about the CPU efficiency of simulating a dynamic environment.
Will Larson also discusses these ideas in a very nuts-and-bolts manner, albeit briefly: http://lethain.com/entry/2007/jun/07/anti-objects-and-reflex...
On the contrary, the ghost object in this example still has to implement the hill climbing algorithm. It could go down the hill (as it would do if pac man got one of the super pellets), or it could ignore the hill altogether. I think this also implies that it could avoid collisions with other ghosts, or even avoid grouping with other ghosts by paying attention to their scent as well. Seems like it would be trivial for a tile to further provide the scent value for all interesting objects in the maze.