Game Theory Meets AI and NLP

AI Machines Have Beaten Moore's Law Over The Last Decade

Before going further, you’ll need to understand the concept of game theory. Game theory is basically a branch of applied mathematics. In-game theories (How Game Theory Strategy Improves Decision Making), there are different available tools with the help of which different situations are analyzed. There are parties in-game theories mostly referred to as players and the decision they have taken are interdependent. This is a kind of playing chess in which the turn of one player is associated with the future strategy of the opponent player.

 

So, a complete strategy, decision, possible movement, and formulation of strategy basically come under the banner of game theory. Game theory is basically a framework with the help of which one can understand the strategy of the opponent player. With the help of optimal game theory, the players come to a point where optimal decision-making is reached and the strategy of the player becomes strong enough so that it can play in any situation with any kind of player. This concept is very important from a technical point of view for those researchers who are willing to work in the field of machine learning, deep learning, AI, or NLP. In this article, the association of game theory with AI and NLP will be discussed.

Game Theory in AI

The main aim behind the game theory is to understand the outcome of the optimal solution of the opponent player. There is another field which is an inverse game theory with the help of which the strategy of the opponent player and strategy can be explained.

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