Evolutionary algorithm (EA) is defined as the set of purpose that used to solve any class of elements puzzle that related to the mathematical rules. Other than that, evolutionary algorithm is one of the problems solving to reduce or maximize a real function by analytically choosing the values of real or integer variables from interior of an allowed set. In artificial intelligence, an EA is a subgroup of evolutionary computation, a general population-based meta-experimental operation algorithm. An EA uses the procedure that inspired by biological progression, such as reproduction, mutation, recombination, and selection.
At the present time, games like Counter Strike Global Offensive and Life or Death 4 always are the most popular games in teenager’s life. Most of the games that nowadays is being popular in the teenager’s life commonly are develop by using Genetic Algorithm (GA). Nevertheless, by using the basic platform of games algorithm which is start from mini games and then into high radius games, interface and quality of the games are transform rapidly. For this case study, mini games are the main topic and an application is genetic algorithm and neural network. The full topic of this case study is Genetic Algorithm and Neural Network for Mini-Games.
For this case study, the main focuses of consideration are physical simulation and character control. Investigation of these issues on computer games used some games which are fitted to explore several aspects of the two main issues. Aim of this case study is also is to build up the controllers then the controller must be able to finish the explicit mission in the two games. The main objective of their case study is controller must be able to gun down and strike the ball with the other two balls one after another. The dare of this game is that the balls have to shot from the suitable point and the goal are to achieve every time. The two virtual characters are fight with each other for the second game. These case studies also show a development method in verifying whether or not the skill powers of the two virtual characters are balanced. Controllers of the both games are progress based on neural network and genetic algorithm in an unsupervised learning manner. This case study more on performs a complete learning on the execution and weaknesses of the controllers.
Evolutionary Algorithm Technique/Method
In this case study, EA techniques are more on the genetic algorithm technique and link together with artificial neural network algorithm. This two technique are developed for energetically change the game difficulty. Its aim is to achieve game balancing or changing game parameters through online learning algorithm.
Physical simulation and character control are two important issues in computer games. In manner to control virtual character to fight with each other in a dynamic environment, some controllers must be developing. In physical...