4-dimensional anti-Kahler manifolds by Kim H.

By Kim H.

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R. 66 Simplified 0 0 0 C1 C1 0 C1 C1 9 10 0:12 0 1:38 1 registers (in effect, knowing the exact composition of the remaining pack); but this is clearly beyond human capability. Less ideal, but difficult nonetheless, is to keep a second, distinct count on which to base play decisions, a possibility suggested by several authors. Even more of a compromise is to use just a single count for both betting and playing decisions, one that optimizes the yield from both together. As an example, advocates of the Hi-Opt counting vector feel it does a better job than the Hi-Lo vector in gaining play advantage.

During each shuffle, reset the running count to zero. As each card is dealt, increment the running count by the corresponding element of the counting vector: if a card of value j is dealt, increment the running count by the j th vector element. (c) Convert the running count into true count. First estimate the number of decks remaining undealt in the shoe. One way is to track the number of rounds dealt since the last shuffle. If Player is the only one at the table, the number of decks used is about one for each nine rounds dealt; with two Players it’s six rounds, with three it’s 5, with four it’s 4.

An alternative and much simpler scheme is “Counter Basic Strategy” (here abbreviated CBS), proposed independently and from different lines of reasoning by Werthamer (2007) and Marcus (2007). To begin, focus on the single counting vector optimized for betting. Rather than each play parameter being individually dependent on true count, instead seek the count-independent Basic Strategy that matches the count-dependent one at a “best” choice of true count. The “best” choice (the “effective true count”) is the one that maximizes Player’s yield, recognizing that he is betting different amounts on different hands.

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