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<?php |
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namespace lucidtaz\minimax\engine; |
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use lucidtaz\minimax\game\GameState; |
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use lucidtaz\minimax\game\Player; |
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/** |
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* Node in the decision search tree |
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* An object of this class can be queried for its ideal decision (and according |
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* score) by calling the decide() method. It will recursively construct child |
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* nodes and evaluate them using that method as well. |
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*/ |
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class DecisionNode |
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{ |
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/** |
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* @var Player The player to optimize for. |
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*/ |
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private $objectivePlayer; |
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/** |
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* @var GameState The current GameState to base future decisions on. |
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*/ |
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private $state; |
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/** |
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* @var int Limit on how deep we can continue to search, recursion limiter. |
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*/ |
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private $depthLeft; |
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/** |
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* @var NodeType Whether we are a min-node or a max-node. This enables the |
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* caller to select either the most favorable or the least favorable |
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* outcome. |
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*/ |
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private $type; |
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/** |
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* @param Player $objectivePlayer The Player to optimize for |
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* @param GameState $state Current GameState to base decisions on |
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* @param int $depthLeft Recursion limiter |
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* @param NodeType $type Signifies whether to minimize or maximize the score |
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*/ |
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public function __construct(Player $objectivePlayer, GameState $state, int $depthLeft, NodeType $type) |
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{ |
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$this->objectivePlayer = $objectivePlayer; |
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$this->state = $state; |
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$this->depthLeft = $depthLeft; |
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$this->type = $type; |
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} |
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/** |
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* Determine the ideal move for this node |
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* This means either the best or the worst possible outcome for the |
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* objective player, based on who is actually playing. (If the objective |
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* player is currently playing, we take the best outcome, otherwise we take |
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* the worst. This reflects that the opponent also plays optimally.) |
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*/ |
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public function traverseGameTree(): TraversalResult |
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{ |
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if ($this->depthLeft == 0) { |
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return TraversalResult::onlyEvaluation($this->makeLeafResult()); |
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} |
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/* @var $possibleMoves GameState[] */ |
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$possibleMoves = $this->state->getPossibleMoves(); |
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if (empty($possibleMoves)) { |
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return TraversalResult::onlyEvaluation($this->makeLeafResult()); |
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} |
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$idealResult = null; |
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$idealMove = null; |
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foreach ($possibleMoves as $move) { |
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$moveResult = $this->getChildResult($move); |
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if ($idealResult === null || $this->isIdealOver($moveResult, $idealResult)) { |
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$idealResult = $moveResult; |
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$idealMove = $move; |
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} |
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} |
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return TraversalResult::create($idealMove, $idealResult); |
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} |
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/** |
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* Formulate the evaluation result, this node being a leaf node |
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*/ |
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private function makeLeafResult(): EvaluationResult |
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{ |
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$result = new EvaluationResult(); |
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$result->age = $this->depthLeft; |
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$result->score = $this->state->evaluateScore($this->objectivePlayer); |
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return $result; |
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} |
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/** |
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* Recursively evaluate a child decision |
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* Apply a move and evaluate the outcome |
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* @param GameState $stateAfterMove The GameState that was created as a |
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* result of a possible move. |
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*/ |
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private function getChildResult(GameState $stateAfterMove): EvaluationResult |
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{ |
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$nextPlayerIsFriendly = $stateAfterMove->getNextPlayer()->isFriendsWith($this->objectivePlayer); |
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$nextDecisionPoint = new static( |
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$this->objectivePlayer, |
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$stateAfterMove, |
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$this->depthLeft - 1, |
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$nextPlayerIsFriendly ? $this->type : $this->type->alternate() |
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); |
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return $nextDecisionPoint->traverseGameTree()->evaluation; |
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} |
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/** |
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* Compare two evaluation results |
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* The meaning of "best" is decided by the "ideal" member variable |
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* comparator |
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*/ |
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private function isIdealOver(EvaluationResult $a, EvaluationResult $b): bool |
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{ |
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$ideal = $this->type == NodeType::MIN() |
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? EvaluationResult::getWorstComparator() |
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: EvaluationResult::getBestComparator(); |
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$idealEvaluationResult = $ideal($a, $b); |
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return $idealEvaluationResult > 0; |
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} |
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} |
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Unless you are absolutely sure that the expression can never be null because of other conditions, we strongly recommend to add an additional type check to your code: