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Benson's Algorithm
Keywords: Life & Death
Benson's algorithm is a rigorous and static (i.e. no search is needed) method for recognizing stones that are uncapturable even if the attacker is allowed to play an infinite number of times in a row (i.e. the defender always passes). This is called unconditional life in Benson's paper [1], a confusing name for something that has no equivalent in traditional Go terminology. The algorithm is only used by a few specific life-and-death programs and modules. Perhaps you could describe the algorithm? I have a rough mental idea of how it would work, but I'm not sure... -- Karl Knechtel jvt: I don't want to paraphrase, so here is a completely rewritten and much simpler version. (See also the revised versions 1 and 2.) "c" stands for Black or White, "-c" for the opposite color. Each point of the board is, of course, either black, white or empty. A c chain is a non-empty maximum connected set of c points. A c region is a non-empty maximum connected set of -c and empty points. A c chain B is unconditionally alive if it is adjacent to at least two c regions R that satisfy:
Note: proof depends on suicide being forbidden by the rules. Sketch of Proof(1) prevents the attacker from filling all liberties of an unconditionally alive chain in 2 adjacent regions, because of the no-suicide rule. (2) prevents the attacker from making liberties by capturing another chain adjacent to the same region. And two liberties ensure the chain will never be in atari. DisclaimerI don't claim these definitions are the same as in the original article [1] by David Benson. Besides I don't define small c-enclosed regions, healthy regions, nor vital regions. The requirement about a c region's interior being filled with -c stones has been intentionally removed because of my different definition of regions. Examples
AshleyF: One confusion I had when I first read the paper was with the discussion of how simply filling liberties (legally) to determine status would still require search. Benson says, "The obvious algorithm for determining whether a block is safe is to attempt to play stones on the intersections. While the full search tree may be pruned by some elementary considerations of inside and outside liberties, in more complex situations the lookahead requirement is still large." Example:
Here, the order of filling liberties is important and even outside vs. inside doesn't help.
AshleyF: I had thought that he was only talking about big eyes where internal liberties may be adjacent to only other empty points, and in that case you could fill without suicide, but no:
He means that the circled point makes it an unsafe eye for the AshleyF: A clarifying example is useful for understanding why the algorithm depends on suicide being disallowed:
This is not unconditionally alive because the marked point is not immediately adjacent to
This, however, is found to be unconditionally alive by Benson's Algorithm. The Of course, though, if suicide is legal then White could clear the stone and be back to the previous diagram. References[1] Benson, D.B., Life in the Game of Go. Information Sciences, Vol.10, pp.17-29, 1976. Reprinted (with corrections) in Computer Games II David N. L. Levy (ed.) Springer-Verlag, 1987 ISBN 0-387-96609-9
[2] Jan: Doesn't this introduce a circularity? Take this example:
There is only one chain, and three regions - one large one and two of one point each. However when I apply the definition, I get the following: The large region doesn't count (not all empty points are adjacent to the chain) so we turn our attention to the two small regions. The first requirement checks out OK, but for the other one, we need to know whether our chain is unconditionally alive. But that was the question we were asking in the first place. I think the second requirement needs to be reworded like this: all other chains adjacent to R are unconditionally alive Did I miss anything here? jvt: You are right. But there is still some indirect circularity remaining because you can have c1 - R1 - c2 - R2 - c1. (c = chain, R = region). Benson uses "transitive closure" to convey the meaning of recursivity without circularity. I am not sure how to express this more clearly. Is "barring circularity" clear enough? Reading again Benson's paper, I see his definition applies to a set of chains, not a single chain, to avoid the circularity problem. My definition needs re-wording: Revised version 1A c chain is unconditionally alive if and only if it is a member of a set S of c chains so that each element B of S is adjacent to at least two c regions R that satisfy:
RemarkNot all empty points in the a c region have to be adjacent to all enclosing c chains. To speak more exactly, to a c chain B in S, there may be empty points not adjacent to in up to N-2 of a total count of N c regions which are adjacent to B. For example:
The marked black chain is adjacent to four "black" regions, so it can be "not adjacent" to some points of two of it. (got confused?)
jvt: of course it can. The two R (R1, R2) are not just any two.
rubilia: I didn't know Benson's article yet, but your revised "unconditional life" criteria is almost exactly what I found in 1993 when I was thinking about the same question. (Probably there are several hundreds of us having "discovered" these laws of unconditional life already :) .) Unfortunately, the definition of "c region" given above is way different from what it has established to be used for in the discussion about unified Though, I do also think that it is not necessary to define Benson's "small c-enclosed", "helthy" nor "vital" regions. Therefore, and for some other reason (see below), I'd suggest the following wording: Revised version 2
A set S of c regions is unconditionally alive if and only if each element B of S is adjacent to at least two distinctive non-c regions R that satisfy:
To implicate that the (at least) two regions (R1, R2, ...) because of which B is unconditionally alive, must not be adjacent to anything else than c regions, I chose all adjacent regions to have to be in S. (That wouln't really be necessary if an adjacent pair of one empty and one -c point inside a non-c region was defined to be "connected", but the term (maximum) "connected" is supposed to be often understood in a different way. So, I like to make it clearer.) rubilia
Here is an example why this is necessary:
Consider (mistakenly) columns b,c,d, including a5, to be R1 and f,g,h, including i5, to be R2.
jvt:
The actual algorithmUsing these criteria "backwards" as an elimination test may be more effective for an algorithm. A graph of regions and chains of the same color is generated, then it's like pulling a thread. False eyes don't satisfy the criteria and get eliminated. That's the way I did it in my Java programming experiments, anyway.
rubilia: To deal with some special cases, this (nice!) algorithm supposingly needs to be modified somehow. jvt: I will make a simplified version of my Java code and post it here in pseudo-code.
See also the Eyes Collection of pages. This is a copy of the living page "Benson's Algorithm" at Sensei's Library. ![]() |