This paper describes the performance of four crossover operators used in evolving the required controllers in a video game. The crossover operators used in this research are the two-point crossover, the uniform crossover, the N-point crossover, and the single-point crossover. The performance of these crossover methods were tested using Infinite Mario Bros game. This video game was chosen due to the dynamicity and complexity of the game. This paper also presents a newly designed nondeterministic based Finite State Machine (FSM) method. The Mario character uses the proposed FSM as its strategy in the game. The proposed FSM is then optimized using a modified Genetic Algorithm (GA). The results showed that the required controllers were generated successfully using the proposed method. The results also showed that the N-point crossover performed well compared to the uniform crossover, the two-point crossover and the single-point crossover methods.
Keywords-Artificial Intelligence (AI); Finite State Machine (FSM); Genetic Algorithm (GA); Infinite Mario Bros; Crossover Methods.I.
Abstract-Psychometric Test has been used as an individual trait measurement for a long time for both experienced entrepreneurs as well as young generation who are looking for their potential in entrepreneurship. The assessment and measurement of strength and weaknesses of key entrepreneurial traits provides the entrepreneurial level and personal development planning for entrepreneur or those who want to venture into business. However, the traditional psychometric test lacks of fun element which is less enjoyable activity during answering the test. Furthermore, it requires basic understanding of business jargon that difficult for certain respondents to provide accurate respond. The purpose of this study is to propose a gamification approach which is mobile game application called 'Freezer' that can measured entrepreneurial traits of the player. In this sense, 'Freezer' creates a simulated scenario for respondents to play as an ice cream business owner and to win as a successful business person, each action done will be measured as entrepreneurial traits criteria. At the end of the game, the result will be presented that can describe the entrepreneurial characteristics of the individuals based on their planning and activities during playing the game.
This paper reviews the use of computer vision methodology in the field of fruit recognition. A fruit recognition process usually consists of three steps which are image acquisition, pre-processing, and image analysis. Various approaches are employed in the pre-processing and image analysis stages and some of these are presented in this paper. This review is conducted in order to understand the current state of the art of these approaches and to study the improvements and the advances in this area. A comparison between these methods will also be discussed.
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