| Summary: | This article presents the development and study of a model for formalizing the decision-making process in a computer game using artificial intelligence methods. Currently, various artificial neural networks and expert systems have been created and used for this purpose.
The analysis of these works showed that these methods show good results, but they have a number of disadvantages, the most significant of which is the complexity of the organization and the long time spent on training the neural network. Thus, the problem of developing new algorithms is posed that is comparable in decision-making speed with artificial neural networks and expert systems and at the same time has less training time. One way to solve this problem is to develop a decision-making model based on an artificial immune system. The aim of the work is to develop and study a model for formalizing the decision-making process in a computer game using artificial intelligence methods.
To demonstrate the possibilities of using the artificial immune system in computer games, the game "dots" was chosen. This game belongs to the category of logical ones, in which only two people can play by default. In this game, positional strategic planning is combined with tactical enumeration of options. To organize the search for a solution in the decision tree, a gaming artificial intelligence was created using methods based on the principles of the immune system.
The artificial immune system is an idealized version of the natural analogue and reproduces the key components of the natural process: selection of the best antibodies in the population depending on the degree of their affinity (proximity) to the antigen, antibody cloning, antibody mutation.
An artificial immune system represents an idealized version of a natural analogue and reproduces the key components of a natural process: selection of the best antibodies in a population depending on the degree of their affinity (proximity) to an antigen, cloning of antibodies, and mutation of antibodies.
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