Evaluation functions in Go take into account both territory controlled, influence of stones, number of prisoners and life and death of groups on the board.
[edit] See also
Computer chess
Computer Go ...
Heuristic evaluation function estimates the cost of an optimal path between a pair of states in a single-agent path-finding problem, . For example, Euclidean or airline distance is an estimate of the highway distance between a pair of locations.
Evaluation Function
In Chess there exist several evaluation functions used to give an estimate of the relative merit of a board configuration.
static evaluation function a function that computes an approximate value of a state (e.g., a position in a board game) without doing any search.
Its evaluation function was initially written in a generalized form, with many to-be-determined parameters (e.g.: how important is a safe king position compared to a space advantage in the center, etc.).
Students were required to write a board evaluation function for use in a search of the move tree.
Pearl (1984) described best-first search as estimating the promise of node n by a "heuristic evaluation function
The full tree for chess has the order of 10120 branches-beyond the reach of any man or computer. There is a fundamental heuristic exchange) between the effectiveness of the evaluation function and the extent of the tree. A very weak evaluation (e.g.
TD-Gammon is a neural network that trains itself to be an evaluation function for the game of backgammon by playing against itself and learning from the outcome.
Bestfirst
search using as the evaluation function and an admissible h function is known as A*
search.
The behavior of A* search
Proof of the optimality of A*
Proof of the completeness of A*
Complexity of A* ...
have done their job we talk about solving such games with minimax and then alpha-beta search. We also discuss the dynamic programming approach, used most commonly for end-games. We also debate the theory and practice of heuristic evaluation functions ...
 See also: AI, Artificial intelligence, Knowledge, Search algorithm, Minimax
  
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