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Introduction to Embedded Intelligent System Lab. at NCCU,
Taiwan
Kao-Shing Hwang, Professor
Dept. of Electrical Engineering
National Chung Cheng University, Taiwan
1. Preface
Embedded Intelligent System Lab is a research laboratory in the Department of Electrical Engineering.
The members consisting of mainly graduate students in electrical engineering, computer science and
engineering, optic-mechatronic engineering and undergraduates of electrical engineering belong to
this lab and carry out research projects. Moreover, this lab works in cooperation with two contributing
laboratories, High Speed Networking and 3D Vision in the Department and the total number of the
staff and students are more than 30.
In this article, Cooperative Autonomous Agents Project, Museum Tour Guide, and Digital Home
Center among the research themes of EIS Lab are described.
2. Cooperative Autonomous Agents with Reinforcement Learning
Multiple agents learn how to cooperate with each other to achieve a good which needs more than one
agent to perform. The theory developed has been applied to robotics and networking congestion
control.
Cooperative robots
Two robots connecting with a straight bar learn how to take action independently to achieve the goal
where the robots is cooperating with each other to pass through a gate.
Congestion control
Cooperative agents learn networking environmental dynamics empirically without prior information
to increase the utilization of available links’ capacity and decrease the ratio of packet loss.
q, u
CMAC
Quantizer
x
Long-term policy evaluator
Expectation
Predictor
(EP)
Action-value
Evaluator
(AE)
W
V
Critic
rˆ
Stochastic
Action
Selector
(SAS)
r
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r for j= 1, K, n;
j≠i
j
n
K
Cooperative
Reward
Generator
Reward
Evaluator
r
qqu , &,
&
reward evaluator
a t
Short-term rate controller

3. Museum Tour Guide Project
The objective of this project is to develop a mobile device for museum touring by which the tourists
can plan their own visit path around exhibitions. Therefore, manpower and related resources of tour
guides can be saved. Besides, the tourists can get real-time and detailed information for the works they
are watching or interested in. The device is designed based on the following the technologies in
networking and embedded systems.
Wireless connections
The mobile device has been equipped with a passive Radio Frequency Identifier (RFID) such that a
visitor can retrieve the information of a work via wireless LAN by its index received by the RFID.
Recently, a new version with an active RFID is being developed at the EIS lab. The hand-set device
can, in addition to providing the information of the works to a visitor approaching his/her interests,
pinpoint the visitor’s location and provide the information about the surroundings information
actively.
Open sources
The development is under the open source platform and utility, such as Embedded Linux for the
computing power, Qt Embedded for GUI, YAFFS for Flash file systems, NFS and networking file
system Coda for connections between the stations.
4. Digital Home Center Project
This project aims at intelligent appliances integrating wireless (802.11 WLAN , Bluetooth, RFID) and
wired (RS-232, RS-485, Power Line Controller) networking technologies to realize an intelligent
networking home system illustrated in the following figure.

Mobile control device
The mobile device functions as a SIP Phone, data storage, IR remote controller, and video/audio
player. In this modern age, the objective of this project is to serve human being for a better life.
5. Conclusion
Wide range of research and development on applications of real-time embedded systems, cooperative
agents system, intelligent chip design, etc, based on machine learning theory and SOC technology are
carried out in this lab. Please refer to web site of the lab for further information. URL:
http://www.eis.ee.ccu.edu.tw
Reference
1. Y. B.Hsu, K. S. Hwang, and J. S. Wang, " An Associative of CMAC for Mobile Robot Motion Control, "Journal
of Information Science and Engineering, Vol. 18, No. 2, pp. 146-161, 2002.(SCI, EI)
2. K. S. Hwang and Y. B. Hsu, “A Self-Improving Fuzzy Cerebellar Model Articulation Controller with Stochastic
Action Generation,” Cybernetics and Systems, An International Journalm,Vol. 33, No. 2, pp. 101-128, 2002.
(SCI, EI)
3. K. S. Hwang and M. J. Ju, “3D Collision-free Motion Based on Collision Index”, Journal of Intelligent &
Robotic Systems, Vol. 33, pp. 45-60, 2002. (SCI, EI)
4. K. S. Hwang and M. Y. Ju, ”A Propagating Interface Model Strategy for Global Trajectory Planning among
Moving Obstacle,” IEEE Transactions on Industrial Electronics, Vol. 49, pp. 1313-1322, No. 6, 2002. (SCI, EI)
5. M. Y. Ju, J. S. Liu and K. S. Hwang, "Real-time Velocity Alteration Strategy for Collision-free Trajectory
Planning of two Manipulators," Journal of Intelligent and Robotic System, Vol. 33, pp. 167-186, 2002. (SCI, EI)
6. K. S. Hwang and M. Y. Ju, ” Speed planning for a Maneuvering Motion," Journal of Intelligent and Robotic
System, Vol. 33, pp. 25-44, 2002. (SCI, EI)
7. K. S. Hwang, Y. B. Hsu, and C. S. Lin, “A Fuzzy CMAC Compensator for the Sliding Control,” the
International journal of Intelligent Automation and Soft Computing, Vol.8, No 3, pp. 273-284, 2002. (SCI)
8. K. S. Hwang and M. Y. Ju, ”Speed Alteration Strategy for Multi-Joint Robots in Co-Working Environment”,

IEEE Transactions on Industrial Electronics, Vol. 50, pp. 385- 393, 2003. (SCI, EI)
9. K. S. Hwang, S. W. Tan, and M. C, Tsai, “Reinforcement Learning to Adaptive Control of Nonlinear systems,”
IEEE Transactions on Systems, man, and Cybernetics-Part B, Vol.33, No.3, 2003. (SCI, EI)
10. Y. B. Hsu and K. S. Hwang, “An Innovative Architecture of CMAC”, IEICE Transactions on electronics, Vol.
E87-C, No. 1, pp.81-93, 2004. (SCI, EI)
11. K. S. Hwang, Y. J, Chen, and K. C. Hong, “Autonomous Exploring System Based on Ultrasonic Sensory
Information,” Journal of Intelligent & Robotic Systems, Vol. 39, pp.307-331, 2004. (SCI, EI)
12. K. S. Hwang, S. W. Tan, and C. C. Chen, ”Cooperative Strategy Based on Adaptive Q-learning for Robot
Soccer Systems,” IEEE transaction on Fuzzy Systems, pp. 569-574, Vol. 12, 2004. (SCI, EI)
13. M. C. Shaio, S. W. Tan, K. S. Hwang, and C. S. Wu, “Co-learning Multi-agent Congestion Control for High
Speed Networks”, WSEAS Transactions on Circuits and systems, Vol. 21, pp.670-675, 2004.(SCI)
14. K. S. Hwang, S. W. Tan, M. C. Shaio, and C. S. Wu, “A reinforcement Learning Approach to Congestion
Control of High-Speed Multimedia Networks," Cybernetics and System, an International Journal, Vo. 36, No. 2,
pp. 181-202, 2005. (SCI, EI)
K. S. Hwang, S. W. Tan, M. C. Shaio, and C. S. Wu, “A Reinforcement Learning Approach to Congestion
Control of High-Speed Multimedia Networks,” IEEE transaction on Systems, man, and Cybernetics-Part B,
Vol.35, No. 2, pp 225-pp268, 2005. (SCI, EI)