Type-2 fuzzified flappy bird control system

Abstract

In this study, we will present the novel application of Type-2 (T2) fuzzy control into the popular video game called flappy bird. To the best of our knowledge, our work is the first deployment of the T2 fuzzy control into the computer games research area. We will propose a novel T2 fuzzified flappy bird control system that transforms the obstacle avoidance problem of the game logic into the reference tracking control problem. The presented T2 fuzzy control structure is composed of two important blocks which are the reference generator and Single Input Interval T2 Fuzzy Logic Controller (SIT2-FLC). The reference generator is the mechanism which uses the bird's position and the pipes' positions to generate an appropriate reference signal to be tracked. Thus, a conventional fuzzy feedback control system can be defined. The generated reference signal is tracked via the presented SIT2-FLC that can be easily tuned while also provides a certain degree of robustness to system. We will investigate the performance of the proposed T2 fuzzified flappy bird control system by providing comparative simulation results and also experimental results performed in the game environment. It will be shown that the proposed T2 fuzzified flappy bird control system results with a satisfactory performance both in the framework of fuzzy control and computer games. We believe that this first attempt of the employment of T2-FLCs in games will be an important step for a wider deployment of T2-FLCs in the research area of computer games

Type-2 Fuzzy Logic Control in Computer Games

“…6. We will handle the bird as the dynamic system to be controlled, the pipe gap as the goal to be tracked via the reference trajectory and the environment generation as uncertainty and disturbance [12].…”

“…Furthermore, collected behavior logs of the human players from their plays might also be a source for social scientists [8]. Consequently, several games have been used as test beds such as Pacman [5], Scrabble [6], Super Mario [9], Counter-Strike [2], StarCraft [10], Flappy Bird [11], [12] and, Lunar Lander [13], [14].…”

“…In this chapter, we will present the novel applications of the IT2-FLCs into the research area of computer games. In this context, we will handle two well-known computer games, namely Flappy Bird [11], [12] and Lunar Lander [13], [14], to show the abilities of the IT2-FLCs. From a control engineering point of view, as the game player can be seen as the main controller in a feedback loop, we will transform the game logic of flappy bird into a reference tracking problem while handling the moon landing problem as a position control problem.…”

Landing on the moon with type-2 fuzzy logic

“…That lies because T2-FLCs using T2 Fuzzy Sets (FSs) are more capable of handling the high levels of uncertainties and nonlinear dynamics associated with real world control applications than its T1 and conventional counterparts [13][14]. The benefits of T2-FLCs are demonstrated in applications such as mobile robots [15,20], flight systems [16], Computing with Words [17], decision making [18] and quite recently in its deployment to the game named Flappy Bird [3].…”

“…Consequently, computational intelligence methods have been used to games such as Counter-Strike [2], Flappy Bird [3], Pacman [4], StarCraft [5], Super Mario [6] and Lunar Lander [7][8][9][10][11]. Lunar Lander is one of most cloned game [12] in the game industry.…”