Overview

Abstract

Our motivation for proposing this initiative includes: (1) attracting more participants to our IEEE CIS conferences and competitions; (2) increasing outreach to undergraduate and high school students through IEEE; and (3) educating young students, including high school, middle school, and undergraduates, via our STEM activities and engaging competitions. The concept involves creating a workshop for young students, coupled with competition, during IEEE-sponsored conferences. This approach has been successfully implemented at IEEE CEC 2023 in the USA, FUZZ-IEEE 2023 in Korea, and the IEEE Region 10 SPNIC Activity on Nov. 18, 2023. At the beginning of the event, or during its initial hours, students will receive educational materials and guidance from tutors and invited speakers on CI-related topics. Subsequently, they will have the opportunity to apply their newfound knowledge in a practical, real-world setting using the QCI&AI-FML Learning Tool (Hardware/Software) provided by IEEE R10, which involves programming QCI&AI-FML robots to accomplish various tasks. On the competition day, we encourage students to form teams, fostering cooperation as they apply their real-world applications.

Competition Goals

The primary aim of our project is to enhance STEM education, with a particular emphasis on Computational Intelligence (CI), for both undergraduate and high school students. Recognizing CI as one of the most promising yet underexplored fields, we have developed heuristic and progressive lessons tailored to students from diverse ages and backgrounds. Our objective is to help students comprehend the real-life applications of CI and understand its increasingly crucial role in the future development of AI technologies.
Additionally, our initiative seeks to attract more scholars to the IEEE WCCI conferences and encourage them to join the IEEE CIS. The QCI&AI-FML theme is central to the IEEE CEC 2023 and FUZZ-IEEE 2023 conferences. We believe that early exposure to CI can draw more students to this research field, potentially leading to their involvement with IEEE CIS. This early engagement could result in these students becoming IEEE CIS members and contributing papers to our flagship CIS conferences at the outset of their academic careers. Moreover, our workshop and its associated competition are designed to garner global scholarly interest in CIS conferences and foster collaborations with companies interested in supporting young scholars.

Competition Rules

We have organized a 3-hour workshop introducing young students to the fundamental concepts of Computational Intelligence (CI) and Quantum CI. Following this, a 3-hour practice session is scheduled, allowing students to apply and refine the knowledge they have gained. The event culminates in a competition to motivate students to use their skills in the real world. After the learning and practice sessions, each team will present their work. They are allocated a total of 10 minutes, which includes a 5-minute presentation followed by a 5-minute question-and-answer session. The evaluation of each team will be based on three criteria: the technical content of their presentation, the quality of the presentation itself, and the responses provided during the Q&A. Each criterion will have a specific weight in the final assessment, ensuring a comprehensive evaluation of the student's understanding and application of CI concepts.

How to submit an entry

The participants will submit their results via the competition website.

How to evaluation

The participants must submit the following files after logging into the competition website.
- Part 1: QCI Data Model (20%)
- Part 2: QCI Inference Model (15%): their original CI knowledge model and CI inference model described by QCI&AI-FML Learning Platform
- Part 3: Fine-Tuned QCI Model (15%): their learned CI knowledge model and CI inference model described by QCI&AI-FML Learning Platform
- Part 4: Onsite Presentation & Q/A (50%): PowerPoint file about the real-world application, QCI&AI Learning Tools Demonstration, and Quantum CI Circuit. After learning, all teams will have 10 minutes, including a 5-minute presentation and a 5-minute Q&A. The evaluation includes Technical Content, Presentation, and Answers to the questions by giving weight to each point.

Six-Step Co-Learning Process for Human and Machine

The six-step co-learning procedure for human intelligence and machine learning inspired by the Heart Sutra is described as follows. Humans and machines learn together through a process of

observing and attending the learning environment (Step 1),
studying the detailed knowledge based on the learner's intelligence (Steps 2 and 3),
utilizing what they have learned (Step 4),
understanding specific domain knowledge (Step 5), and finally
explaining it to new learners (Step 6).
This interaction is repeated continuously to achieve the goal of co-learning between humans and machines.
IEEE R10 EAC & 2023 CIS Education Portal Event Video

03252023-IEEE R10 EAC & 2023 CIS Education Portal Event (No. 5) (3:45)

10062023-PSO-based CI Agent with Learning Tool for Student Experience in Real-World Application (2:54)

Registration Deadline

Registration must be received before May 31, 2024(Extended) via the competition website (Register Form).

Available Software Tools

VisualFMLTool : It can be executed on platforms containing the Java Runtime Environment. The Java Software Development Kit, including JRE, compiler and many other tools can be found at here. The VisualFMLTool can download from here and then to extract it. Then it is only needed to click the file VisualFMLTool.bat included in the zip to execute the tool.
QCI&AI-FML Learning Platform : It is developed by KWS center/OASE Lab., NUTN, Taiwan and can be executed on different platforms online. After registering the competition, we can provide an account for the participants.
ZAI-FML Learning Platform : It is developed by Zsystem Co. Ltd., Taiwan and can be executed on different platforms online. The participants can apply for a trial account online.
JFML : A spanish research group (Jose Manuel Soto Hidalgo, Giovanni Acampora, Jesus Alcala Fernandez, Jose Alonso Moral) has released a library for FML programming that is very simple to use and compliant with IEEE 1855. JFML can download from here. Additional information about the library is here.
Some References associated to JFML
- J. M. Soto-Hidalgo, Jose M. Alonso, G. Acampora, and J. Alcala-Fdez, "JFML: A Java library to design fuzzy logic systems according to the IEEE Std 1855-2016," IEEE Access, vol. 6, pp. 54952-54964, 2018.
- J. M. Soto-Hidalgo, A. Vitiello, J. M. Alonso, G. Acampora, J. Alcala-Fdez, "Design of fuzzy controllers for embedded systems with JFML," International Journal of Computational Intelligence Systems, vol. 12, no. 1, pp. 204-214, 2019.

Reference

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