On Quantifying of Learning Creativity Through Simulation and Modeling of Swarm Intelligence and Neural Networks Hassan. M. Mustafa Computer Engineering Department, Faculty of Engineering, Al-Baha University Al-Baha, Kingdom of Saudi Arabia E-mail: mustafa_hasan47@yahoo.com Turki F. Al-Somani Computer Engineering Department, Faculty of Engineering Al-Baha University Al-Baha, Kingdom of Saudi Arabia Email: tfsomani@uqu.edu.sa Ayoub Al-Hamadi Institute for Electronics, Signal Processing and Communications (IESK) Otto-von-Guericke-University Magdeburg-Germany E-Mail : Ayoub.Al-Hamadi@ovgu.de Abstract—This research work presents a systematic investigational study of an interesting challenging phenomenon observed in natural world. Mainly, presented study concerned with conceptual interdisciplinary analysis and evaluation of quantified learning creativity phenomenon. Associated with diverse aspects of measurable behavioral learning performance. That's observed by two diverse natural biological systems' models (human & non-human creatures). Specifically, introduced study of two biological models consider comparison of quantified learning creativity phenomenon. That's observed during human interactive tutoring / learning processes with environment. Versus ecological behavioral learning of swarm intelligence agents (Ants), during performing foraging process. Furthermore, presented comparative study inspired by naturally realistic models of Artificial Neural Network (ANN) and Swarm Intelligence. Interestingly, obtained simulation and modeling results have announced that learning performance curves of either models behave with close similarity to each other. More precisely, analysis and evaluation of learning performance curves of two diverse biological models revealed that both obey exponentially decayed learning curves; following least mean square (LMS) error algorithm. Keywords- learning creativity phenomenon; Synaptic Plasticity; Brain functional modeling; Artificial Neural Network Modeling; Learning Creativity; Ant Colony Systems; and Computational Biology. I. INTRODUCTION This piece of research inspired by a strong belief that interdisciplinary combination of Neural Networks models with cognitive learning theories and neuroscience contributes innovative investigations of essential educational issues. More specifically, systematic investigational study of quantified human learning creativity phenomenon is considered as an interdisciplinary, challenging, and interesting educational issue. In more details, human creativity phenomenon is observable while practicing interactive face to face tutoring sessions at classrooms. In other words; learning creativity phenomenon is detectable at educational field practice, during performing mutual bidirectional feedback (input stimulation / output response) between tutor and learner. Herein, this paper adopts realistic simulation and modeling of two relatively new creativity disciplines concerned with (humans & non-humans). Accordingly, it presents an investigational comparative study of observed learning creativity phenomenon associated with both creativity disciplines. They are namely: swarm intelligence, and neural networks which are modeled realistically aiming to reach innovative quantitative investigational study of observed creatures' creativity phenomenon in nature. Presented creativity models are tightly related with behavioral learning convergence observed by humans (neural) and Ant Colony System (non neural) [1][2]. By more details, at one hand Artificial Neural Networks (ANN S ) modelling discipline has been adopted for realistic modeling of quantified human learning creativity phenomenon. So, presented ANN S models have been designed and implemented on the bases of optimal selectivity of two ANN S design parameters. Namely : gain factor value (of Sigmoid activation function); and learning rate parameter value. Furthermore, optimal choice of hidden neurons' number relevant for enhancement of quantified learning creativity. Conclusively, presented simulation and modeling results for either learning paradigms seemed to be promising for more elaborate future, systematic , and innovative applied research in evaluation and enhancement of human learning creativity phenomenon [3-6]. On the other hand, ecological behavioral learning of Ant Colony System (ACS), with type namely : Temnothorax albipennis (formerly Leptothorax albipennis) is considered. Its individual agents (ants) adopt the natural intelligent teaching technique known as tandem running. Briefly, the type of ACS adopting (tandem running technique) performs its behavioral learning function 978-1-61284-641-5/11/$26.00 ©2011 IEEE 2011 IEEE Global Engineering Education Conference (EDUCON) – "Learning Environments and Ecosystems in Engineering Education" April 4 - 6, 2010, Amman, Jordan Page 330