Computational Intelligence Course in Undergraduate Computer Science and Engineering Curricula

Computational Intelligence (CI) is the study of adaptive mechanisms to enable or facilitate intelligence behavior in complex, uncertain and changing environments(1). These adaptive mechanisms include those artificial intelligence paradigms that exhibit an ability to learn or adapt to new situations, generalize, abstract, discover and associate(1). The paradigms of CI are inspired from biology and nature. These paradigms include neural networks, evolutionary computing, swarm intelligence, fuzzy systems, and artificial immune systems(6). Computational Intelligence is one of the most actively researched areas in computer science and engineering. The field of CI is making contributions and has applications within several disciplines including biology, computer science, chemistry, economics, electromagnetics, immunology, information science, robotics, control engineering and automation, industrial fault diagnosis, linguistics, material science, music, and physics(6). Educational excellence requires exposing students to the current edge of research. To ensure that student projects are along the same trajectory that the industry is moving, educators must continually introduce emerging techniques, practices, and applications into the curriculum. The field of computational intelligence is growing rapidly. It is essential that the emerging field of computing intelligence be integrated into the computer science and engineering curriculums. This paper is a study of different approaches that are used by different institutions of higher education around the world to integrate computing intelligence concepts in their computer science and engineering curriculum.