The banker bot does not hash, it collects compact polynomial representations of the probability distribution in the branch. So the accumulation of the polynomials generates a successive set of combinatoric that meet the control flow constraint. And there is a bunch of theory along with that which comes from high paid mathematicians.
The banker bot is also a very old, and well known algorithm; in common use with no ownership claim known. It cannot have a patent.
But, back to banker. For banker bot, that tree is a decoding/encoding tree; encode up, decode down. The leaves get raw prices, each price parsed from leave to root; higher price bets to lower price bets. The root generates the encoded gain or loss back down. That is what I have in a banker bot network. It should ultimately, do a Lagrange number shifts high, going up. Each polynomial a function of the previous.
The theory should be something like: The two period adaption meets the Shannon banwidth limit, hence encoding/decoding apply. The graph is a compact polynomial, is minimally redundant and adapts to the Shannon condition of maximum entropy. That makes it hyperbolic. The graph undergoes non-adiabatic change when rank changes. Hire a mathematicians, they make very good bot algorithms.
In economics, the banker graph is the belief function that Roger Farmer talks about. The accumulated polynomial is the graph generator of what the agents does. From the neural point of view, that model is exact, neurons form the minimal rate reduction graph which generates human actions, in sequence. Shopping habits is a multi modal rate counter, adapting toward a common finite ratio, low order, power series; a shopping clock.
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