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Bounded Look Ahead Strategy and Use of EF by Ms. Bidyulata Sahoo

Bounded Look Ahead Strategy and Use of EF by Ms. Bidyulata Sahoo | IARE | #ArtificialIntelligence #BoundedLookAhead #EvaluationFunction #GameAI #AdversarialSearch #StrategicPlanning #AIAlgorithms #Minimax #GameStrategy #aireasoning

Description: The Bounded Look Ahead Strategy in Artificial Intelligence (AI) is a decision-making technique used in game playing and problem-solving, where the search is limited to a fixed number of levels or moves ahead. It reduces computational complexity while still enabling smart choices. The Evaluation Function (EF) is used to assess the desirability of a game state when a full search is not possible. Together, these tools enable efficient, real-time decisions in adversarial search environments like chess, tic-tac-toe, or other strategic games.

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Bounded look ahead strategy, evaluation function, game tree pruning, AI decision making, adversarial search, game state evaluation, limited depth search, heuristic analysis, game AI, strategy planning

#ArtificialIntelligence #BoundedLookAhead #EvaluationFunction #GameAI #AdversarialSearch #StrategicPlanning #AIAlgorithms #Minimax #GameStrategy #AIReasoning

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