Dear Eric,

Initially, we just at the border node S (18).

After expanding the node S, the border is with A (19), B (22).

Node A is the smallest of the border.

After expanding A, the border is with B (22), G (34)

Node B is the smallest of the border.

After expanding B, the border is with G (25)

Node G is the smallest of the border.

You finish the algorithm when the node G is the smallest of the border not
when he enters the boundary

Wladimir Araujo Tavares
*Federal University of CearĂ¡

*




On Fri, May 13, 2011 at 6:14 PM, xuwenduan <xuwend...@gmail.com> wrote:

> I have an answer for my own question:
>
> I think I've misunderstood the statement in the book, which says:
>
> ...to ensure that the optimal path to any repeated state is always the
> first one followed.
>
> in the above example, we haven't actually started to follow (expand) G
> yet, so the statement about consistency is still valid.
>
> wenduan
>
> On May 13, 7:56 pm, eric <xuwend...@gmail.com> wrote:
> > Hi All,
> >
> > A* search with consistent heuristics is supposed to ensure that an
> > optimal path to a repeated state is always the first path generated,
> > but consider the following example:
> >
> >               /---4--->A(h=15)--30-->\
> > S(h=18)                                        G (h=0)
> >               \ ---5--->B(h=17)--20-->/
> >
> > where S and G are the start and goal nodes respectively, in this case
> > G is a repeated state which is also the goal state, but carry out A*
> > on the above graph, we get:
> >
> > Expand S: get children A (f = 4 + 15 = 19) and B (f = 5 + 17 = 22),
> > and A has a smaller f value, we next expand A
> > Expand A: get child G (f = 34 + 0 = 34)
> >
> > at this point we obviously have a sub-optimal path to G with cost 34 >
> > the optimal cost of 5 + 20 = 25?
> >
> > Is this just a special case where the goal is also a repeated state or
> > am I missing something here?
> >
> > Thanks in advance.
> > e.
>
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