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Hands-on experiments on intelligent behavior for mobile robots

Authors :
Cuevas, Erik
Zaldivar, Daniel
Perez-, Marco
Ramirez, Marte
Source :
International Journal of Electrical Engineering Education 48 (1), (2011), pp. 66-78
Publication Year :
2014

Abstract

In recent years, Artificial Intelligence techniques have emerged as useful tools for solving various engineering problems that were not possible or convenient to handle by traditional methods. AI has directly influenced many areas of computer science and becomes an important part of the engineering curriculum. However, determining the important topics for a single semester AI course is a nontrivial task, given the lack of a general methodology. AI concepts commonly overlap with many other disciplines involving a wide range of subjects, including applied approaches to more formal mathematical issues. This paper presents the use of a simple robotic platform to assist the learning of basic AI concepts. The study is guided through some simple experiments using autonomous mobile robots. The central algorithm is the Learning Automata. Using LA, each robot action is applied to an environment to be evaluated by means of a fitness value. The response of the environment is used by the automata to select its next action. This procedure holds until the goal task is reached. The proposal addresses the AI study by offering in LA a unifying context to draw together several of the topics of AI and motivating the students to learn by building some hands on laboratory exercises. The presented material has been successfully tested as AI teaching aide in the University of Guadalajara robotics group as it motivates students and increases enrolment and retention while educating better computer engineers.<br />Comment: 11 Pages

Subjects

Subjects :
Computer Science - Robotics

Details

Database :
arXiv
Journal :
International Journal of Electrical Engineering Education 48 (1), (2011), pp. 66-78
Publication Type :
Report
Accession number :
edsarx.1407.0051
Document Type :
Working Paper