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of precisely m members of these intervals where m is defined in terms of
For
the interval greedy game the basic idea is simpler; RED divides I into an appropriate
number of intervals and chooses one of them suitably modified.
α
and n
.
β =
,
=
When
0
the greedy length game in which k
1 and the interval length
game in which
α =
0 have a common solution so we now investigate the point
greedy interval game
Γ
in which RED chooses an interval, BLUE chooses a point
and
In common with Ruckle, we take the interval to be closed so that RED
will in general have only
β
0
.
-optimal strategies although it will be plain that RED
has optimal strategies if open intervals are allowed. The next lemma generalises the
strategies used by Ruckle in the game with
ε
β =
0 to obtain bounds on what the
players can achieve in the more general game.
Lemma 1. In the point greedy interval game, BLUE can restrict RED's expectation
to at most 1
/ (
4
(
1
+ β ))
whereas RED can guarantee an expectation of at least
n 2
{ (
β ) /
}− ε
ε >
max
n
1
where
0 and the maximum is taken over all positive
integers.
Proof. If BLUE employs the uniform distribution on I
then BLUE has a probability
of L of intersecting with a RED interval of length L giving RED an expectation of
(
,
1
L
)
L
L
β
L
=
L
(
1
(
1
+ β )
L
) .
Hence the best that RED can do is to choose an
interval of length 1
/ (
2
(
1
+ β ))
and BLUE can restrict RED to a payoff of at most
1
/ (
+ β )) .
For a positive integer n and
4
(
1
η >
0 small, suppose RED plays one of the intervals
[
1 at random; any pure strategy of BLUE can
intersect at most one of these intervals so RED can ensure an expectation of at least
k
/
n
, (
k
+
1
) /
n
η ] ,
k
=
0
,
1
,...,
n
1
n η )(
n
1
1
n (
1
n η )=
n
β
n 2
1
n
1
β
(
) β
η
n
n
and the lemma follows.
A consequence of the lemma is that, if there is a positive integer n such that
n 2
(
then its common value is the value of the game. It
is therefore easy to check that, for all positive integers n
n
1
β ) /
=
1
/ (
4
(
1
+ β )) ,
2
,
thegamehasvalue
1
/ (
.
The formulation of the game requires that the players know the value of
2 n
)
when
β =(
n
2
) /
2
but,
from a practical view, BLUE in particular may have little idea concerning its precise
value. It can therefore be useful to know that a strategy is reasonably good for a
range of values of
β
even it is not optimal, particularly if that strategy is fairly
simple. The above analysis suggests the uniform distribution is such a strategy; in
particular, it is likely to be effective if the loss of material has serious implications
for RED, that is, when
β
β
is large.
the position is a good deal more complicated.
First of all we should perhaps address the question of whether the games actually
have a value; we do not wish to go into the details here but they do by an existence
theorem of Alpern and Gal (see [ 5 ] Theorem A.1 on page 293). In the games in
For general values of
β [
0
,
1
] ,
 
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