Principles from Basic Endgame Trees (Daniel Hu)
Posted: Tue Apr 20, 2021 9:43 am
This thread discusses the paper Principles from Basic Endgame Trees of Daniel Hu.
https://dhu163go.files.wordpress.com/20 ... ciples.pdf
Currently, I refer to its version on 2021-04-17. So far, I have only looked briefly into the paper and it may be a long time before I find time to read and understand it to its end. Nevertheless, I start discussion now because I have some questions whose answers might ease my further reading. Citation from page 1 with sentence numbers added by me:
"[1] we calculate the miai value of a node as the average of the miai value of its two children. [2] The miai value of a leaf node is simply the score there. [3] This recursively defines miai value for every node. [4] We continue by defining the miai value of a move as the difference between the miai values of the final node and starting node. [5] Note that miai values of sibling moves are equal. [...] [6] we will assume that in all binary trees, follow up moves have a lower miai value than preceding MOVES"
[1][2] define "miai value OF A NODE" as the average of the children's miai values and for a leaf as the score. This suggests that 'miai value OF A NODE' shall mean 'count'.
The recursion in [3] only makes sense if we already presume [6]. Since [6] appears later in the text, I wonder whether this is indeed the assumption for [3].
Is [6] a general presupposition for the entire paper? If yes, then why does the paper claim to introduce miai counting when it would only consider game trees with decreasing(-or-constant) miai values OF MOVES?
[4] defines "miai value OF A MOVE" as the difference between the miai values of the final NODE and starting NODE. I suppose "starting node" means the position left by the move and "final position" means the position created by the move. As a consequence of the definition of a miai value OF A NODE and its relying on [6], this definition also appears to presume [6].
The definition of miai value OF A MOVE is not the usual definition of move value of miai counting and is not the definition of gain. For Black's move, the definition of miai value OF A MOVE equals the definition of Black's gain. For White's move, the definition of miai value OF A MOVE equals the definition of the negation of White's gain, that is, a negative value. Is the definition as intended or has it been careless?
Supposing the miai value OF A MOVE was intended to be defined as gain, then the author's claim of it being part of miai counting again seems to presume [6]. Since [6] appears later in the text, I wonder whether this is indeed the assumption for [4].
If this is the intention indeed, then move value equals Black's gain and equals White's gain (*) so that miai value OF A MOVE can be defined as gain AS LONG AS WE PRESUME [6]. As soon as we drop [6], miai value OF A MOVE should be defined as move value.
[5] states "miai values of sibling MOVES are equal". I assume this refers to a node's moves to the black child and white child. Then, [5] expresses (*).
EDIT
https://dhu163go.files.wordpress.com/20 ... ciples.pdf
Currently, I refer to its version on 2021-04-17. So far, I have only looked briefly into the paper and it may be a long time before I find time to read and understand it to its end. Nevertheless, I start discussion now because I have some questions whose answers might ease my further reading. Citation from page 1 with sentence numbers added by me:
"[1] we calculate the miai value of a node as the average of the miai value of its two children. [2] The miai value of a leaf node is simply the score there. [3] This recursively defines miai value for every node. [4] We continue by defining the miai value of a move as the difference between the miai values of the final node and starting node. [5] Note that miai values of sibling moves are equal. [...] [6] we will assume that in all binary trees, follow up moves have a lower miai value than preceding MOVES"
[1][2] define "miai value OF A NODE" as the average of the children's miai values and for a leaf as the score. This suggests that 'miai value OF A NODE' shall mean 'count'.
The recursion in [3] only makes sense if we already presume [6]. Since [6] appears later in the text, I wonder whether this is indeed the assumption for [3].
Is [6] a general presupposition for the entire paper? If yes, then why does the paper claim to introduce miai counting when it would only consider game trees with decreasing(-or-constant) miai values OF MOVES?
[4] defines "miai value OF A MOVE" as the difference between the miai values of the final NODE and starting NODE. I suppose "starting node" means the position left by the move and "final position" means the position created by the move. As a consequence of the definition of a miai value OF A NODE and its relying on [6], this definition also appears to presume [6].
The definition of miai value OF A MOVE is not the usual definition of move value of miai counting and is not the definition of gain. For Black's move, the definition of miai value OF A MOVE equals the definition of Black's gain. For White's move, the definition of miai value OF A MOVE equals the definition of the negation of White's gain, that is, a negative value. Is the definition as intended or has it been careless?
Supposing the miai value OF A MOVE was intended to be defined as gain, then the author's claim of it being part of miai counting again seems to presume [6]. Since [6] appears later in the text, I wonder whether this is indeed the assumption for [4].
If this is the intention indeed, then move value equals Black's gain and equals White's gain (*) so that miai value OF A MOVE can be defined as gain AS LONG AS WE PRESUME [6]. As soon as we drop [6], miai value OF A MOVE should be defined as move value.
[5] states "miai values of sibling MOVES are equal". I assume this refers to a node's moves to the black child and white child. Then, [5] expresses (*).
EDIT