Tree search
- From: kingpin@xxxxxxxxxxx
- Date: 31 Aug 2006 04:16:08 -0700
Hi to all,
you have a problem. Its search speace is modeled with a tree with
finite height. You have an evaluation function (heuristic) that says,
at every level i of the tree, if a node is better than another. The
heuristic is not perfect in the sense that it has some error. The
solutions is a path from the root to a node on the leaves that has some
property. Obviously, you don't heave enough information to decide
anything else: you must search.
I want to use A* (or best-first search) and study the aveage number of
nodes expandend before a solution is found.
How should i proceed? How should i specify the error the heuristic make
in order to simplify the analysis?
For example: the heuristic h is strictly monotonic, the tree is binary
and the problem is a minimization one.
I start to search with a b-f search. If, at level i, i make the wrong
decisions, i must search the whole sub-tree rooted at the son selected
before i can use the right node:
[i] level i
| \
| \
[1] [2] sons of level i
Since h([1]) < h([2]), than for every node n in the subtree rooted at
[1], h(n) < h([2]).
So, the "delay" is exponential....
I'am interested in the case that h is not strictly monotonic....
Any suggestion? Any paper? Any book?
Thank you,
Lucas
.
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