Workshop on AIoT (III)
Topic: AIoT-FML BCI Application
Purpose
This purpose of this workshop is to understand fuzzy systems, machine learning and optimization through the development of a simple application like a BCI using the AI-FML learning platform developed by National University of Tainan (NUTN), Taiwan.
Methods
In this AIoT workshop, we focus on a BCI based on a fuzzy system.
The fuzzy system looks for the emotional prediction according to the individual conditions such as the degree level of attention, rational, sensual fatigue and stress by pairing a BCI device.
The control rules are optimized by particle swarm optimization (PSO) which is one of the popular population-based stochastic optimization techniques.
Tasks
In this workshop, the participants will be divided into small groups. For example, each group is composed of both Taiwanese students (2-3 persons) and Japanese students (2-3 persons). Additionally, each group has the following tasks.
Examine the effect of various parameters of fuzzy systems (e.g., the rule base, the number of membership functions) and PSO (e.g., the number of particles and the number of fitness evaluations) on the learning performance.
Design its own expressions of robots according to the outputs of the fuzzy system.
Present or make a short report on what they learned at the end of the workshop.
08172021-Workshop on AIoT (III) AIoT-FML Application for BCI