Difference between revisions of "MCαβ"

From Chessprogramming wiki
Jump to: navigation, search
(One intermediate revision by one other user not shown)
Line 2: Line 2:
  
 
'''Monte-Carlo Alpha-Beta''', '''(MCαβ)'''<br/>
 
'''Monte-Carlo Alpha-Beta''', '''(MCαβ)'''<br/>
is a [[Best-First|Best-First search]] algorithm based on [[Monte-Carlo Tree Search]] and a shallow [[Alpha-Beta|alpha-beta]] [[Depth-First|depth-first-search]]. It is used in [[Lines of Action]] and in conjunction with [[UCT]] (Upper Confidence bounds applied to Trees) also in Chess. It is similar to the the Best-First Minimax-Search proposed by [[Richard Korf]] and [[Max Chickering]] <ref>[[Richard Korf]], [[Max Chickering]] ('''1996'''). ''[https://www.microsoft.com/en-us/research/publication/best-first-minimax-search/ Best-First Minimax Search]''. [https://en.wikipedia.org/wiki/Artificial_Intelligence_(journal) Artificial Intelligence], Vol. 84, No 1-2</ref>.
+
is a [[Best-First|Best-First search]] algorithm based on [[Monte-Carlo Tree Search]] and a shallow [[Alpha-Beta|alpha-beta]] [[Depth-First|depth-first-search]]. It is used in [[Lines of Action]] and in conjunction with [[UCT]] (Upper Confidence bounds applied to Trees) also in Chess. It is similar to the the [[Best-First Minimax Search|Best-first minimax search]] proposed by [[Richard Korf]] and [[Max Chickering]] <ref>[[Richard Korf]], [[Max Chickering]] ('''1996'''). ''[https://www.microsoft.com/en-us/research/publication/best-first-minimax-search/ Best-First Minimax Search]''. [https://en.wikipedia.org/wiki/Artificial_Intelligence_(journal) Artificial Intelligence], Vol. 84, No 1-2</ref>.
 
<span id="Four Phases"></span>
 
<span id="Four Phases"></span>
 
=Four Phases=  
 
=Four Phases=  
Line 13: Line 13:
 
=See also=
 
=See also=
 
* [[Alpha-Beta]]
 
* [[Alpha-Beta]]
 +
* [[Best-First Minimax Search]]
 
* [[Minimax]]
 
* [[Minimax]]
 
* [[Monte-Carlo Tree Search]]
 
* [[Monte-Carlo Tree Search]]

Revision as of 12:58, 11 February 2019

Home * Search * MCαβ

Monte-Carlo Alpha-Beta, (MCαβ)
is a Best-First search algorithm based on Monte-Carlo Tree Search and a shallow alpha-beta depth-first-search. It is used in Lines of Action and in conjunction with UCT (Upper Confidence bounds applied to Trees) also in Chess. It is similar to the the Best-first minimax search proposed by Richard Korf and Max Chickering [1].

Four Phases

MCαβ can be divided into four strategic phases, repeated as long as there is time left:

  1. In the Selection phase the tree is traversed from the root node until it selects a leaf node that is not added to the tree yet
  2. The Expansion strategy adds the leaf node to the tree
  3. The Playout phase performs a shallow alpha-beta search
  4. The Backpropagation strategy propagates the results through the tree

See also

Publications

Forum Posts

External Links

feat. Mike Lawrence, Alphonse Mouzon, John Lee, Mike Mandel

References

Up one level