The Minimax algorithm is the most well-known strategy of play of two-player, zero-sum games. The minimax theorem was proven byJohn von Neumannin 1928. Minimax is a strategy of always minimizing the maximum possible loss which can result from a choice that a player makes. ...
Using Alpha-Beta Pruning to Improve the Computational Efficiency of a Minimax AI The minimax algorithm is used to choose the best-case scenario from all possible scenarios or a subset thereof. One of its more interesting use-cases is the AI opponent in turn-based games like tic-tac-toe, che...
Most business owners and content creators are familiar withAI-written contentby OpenAI’s ChatGPT. People generate content bytalking to the GPT algorithm, which is a language learning model. When detecting AI writing, the same language learning model is applied. ...
Alpha-beta (AB) pruning is an improvised version of the Minimax algorithm. The search optimization technique employed by this pruning algorithm cuts down the spread of search and reduces the computation time considerably. Minimax algorithm exhaustively reviews all the nodes in the search tree for max...
Minimax algorithm run on the game-tree from the previous image. In this case, the evaluation is minimised on the engine’s turn as it is playing as Black. The evaluation of the position is -4. Source: Author. Finally, a pruning algorithm called alpha-beta pruning is applied...
An online reinforcement learning algorithm is anytime if it does not need to know in advance the horizon T of the experiment. A well-known technique to obtain an anytime algorithm from any non-anytime algorithm is the "Doubling Trick". In the context of adversarial or stochastic multi-armed...
The main contribution of this paper is to propose a proper mathematical definition of local optimality for this sequential setting---local minimax, as well as to present its properties and existence results. Finally, we establish a strong connection to a basic local search algorithm---gradient ...
What is Deepfake in Artificial Intelligence? In a generation in which technological advancements are hastily reshaping our lives, synthetic intelligence (AI) has emerged as an effective device able to both excellent innovation and capability misuse. Among the interesting yet regarding applications of AI...
This is because more complex plans typically involve smaller and more irregular beam apertures, larger tongue-and-groove effects and larger modulation of machine parameters. Such complexities affect the uncertainties in dose calculations due to limitations in the calculation algorithm or in the beam ...
i) Dilated convolutionsexpand the receptive field without requiring a larger kernel or additional parameters. This is useful for capturing long-term dependencies in datasets. ii) Sparse Sampling:Dilated convolutions create gaps in the convolutional kernel, which minimizes the amount of computing required...