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In computer science, a binary decision diagram (BDD) or branching program is a data structure that is used to represent a Boolean function. On a more abstract level, BDDs can be considered as a compressed representation of sets or relations .
Multiway branch is the change to a program's control flow based upon a value matching a selected criteria. It is a form of conditional statement.A multiway branch is often the most efficient method of passing control to one of a set of program labels, especially if an index has been created beforehand from the raw data.
[a] Branch (or branching, branched) may also refer to the act of switching execution to a different instruction sequence as a result of executing a branch instruction. Branch instructions are used to implement control flow in program loops and conditionals (i.e., executing a particular sequence of instructions only if certain conditions are ...
A branch table allows the switch statement to determine with a small, constant number of instructions which branch to execute without having to go through a list of comparisons, while a binary search takes only a logarithmic number of comparisons, measured in the number of cases in the switch statement.
Branch prediction attempts to guess whether a conditional jump will be taken or not. Branch target prediction attempts to guess the target of a taken conditional or unconditional jump before it is computed by decoding and executing the instruction itself. Branch prediction and branch target prediction are often combined into the same circuitry.
If-then-else flow diagram A nested if–then–else flow diagram. In computer science, conditionals (that is, conditional statements, conditional expressions and conditional constructs) are programming language constructs that perform different computations or actions or return different values depending on the value of a Boolean expression, called a condition.
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The rating of best Go-playing programs on the KGS server since 2007. Since 2006, all the best programs use Monte Carlo tree search. [14]In 2006, inspired by its predecessors, [15] Rémi Coulom described the application of the Monte Carlo method to game-tree search and coined the name Monte Carlo tree search, [16] L. Kocsis and Cs.