Applications of Artificial Intelligence in Game Theory

Abstract

This topic is an area of research related to the application of artificial intelligence methods in game theory. The aim of the research is to create effective algorithms and models to analyze various game scenarios and predict optimal decisions for players. To achieve this goal, various methods of machine learning are used, as well as algorithms for optimization and statistical analysis of data. The relevance of this topic is due to the increasing popularity and importance of games in our lives, as well as the possibility of applying the results in various fields such as economics, business, politics, etc. The study was conducted with the help of computer implementation, which allows us to test the algorithms on different game scenarios and evaluate their results. The results confirm the effectiveness of the developed methods and algorithms.

The conclusion of the work summarizes the results of the study and discusses possible directions for further work in this area. This work may be useful for specialists in the field of artificial intelligence and game theory, as well as for developers of game applications.

Keywords: Game Theory, Artificial Intelligence, reinforcement learning, Q-learning, deep learning, neural networks, decision-making algorithms, strategies.