2011 IEEE Workshop on Robotic Intelligence in Informationally
Structured Space (RiiSS2011) will bring together scientists,
engineers and students from around the world to discuss the latest
advances in the field of robot intelligence within the context of
informationally structure space. Recently, the emerging synthesis of
information technology (IT), network technology (NT), and robot
technology (RT) is one of the most promising approaches to realize a
safe, secure, and comfortable society for the next generation.
Human-centered systems require, in particular, sophisticated
physical and information services which are based on sensor
networks, ubiquitous computing, and intelligent artifacts.
Information resources and the accessibility within an environment
are essential for people and for robots. The environment surrounding
people and robots should have a structured platform for gathering,
storing, transforming, and providing information. Such an
environment is called informationally structured space.
The intelligent computing for the design and use of the
informationally structured space should be discussed from various
points of view at the same time. An intelligent robot can be an
interface connecting between people and informationally structured
space to search and provide information. Computational intelligence
plays an important role in dealing with perception, action, decision
making, planning, adaptation, and learning of robots in the
informationally structured space.
The IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS 2013) focuses on the intelligence emerging from the synthetic integration of IT, NT, and RT in the informationally structured space. Topics for contributions include, but may not be limited, the following researches:
Please forward your proposals with detailed abstract and bio-sketches of the speakers to Workshop Co-Chairs and SSCI Keynote-Tutorial Chair, Dr S Das.
#1. Kukanchi - interactive human-space
design and intelligence
Kazuyoshi Wada (Tokyo Metropolitan University,
Japan, k_wada@sd.tmu.ac.jp)
Mihoko, Niitsuma (Chuo
University, Japan,
niitsuma@mech.chuo-u.ac.jp)
Recently, the integration of information
technology, network technology, and robot technology has discussed
from various points of view. This special session discusses on
Kukanchi: interactive human-space design and intelligence where
humans and robots coexist symbiotically using information embedded
in the environment. The extremely large volume of information and
functions served by Kukanchi could be beyond human's ability of
information processing. A problem is how to connect human's senses
(modalities) to Kukanchi smoothly. To solve the problems, we can
introduce the concept of augmented embodiment from three synthetic
approaches; a) Cognitive self: modeling subjective perception using
robot systems etc., b) Interactive self: modeling interactive events
observed by intelligent space etc., and c) Symbolic self: describing
representations of human and space using ontology etc. Topics for
contributions include, but may not be limited, the following
researches:
- Robot Companions and Social Robots in Home
Environment
- Service Robots
- Physical Human-Robot Interaction
- Sensor Networks
- Structuralization of Environmental Information
#2. Intelligent Behavior Learning of
robots
Kazuo Kiguchi (Kyushu University, Japan <kiguchi@mech.kyushu-u.ac.jp>)
Futoshi Kobayashi (Kobe University, Japan
<futoshi.kobayashi@port.kobe-u.ac.jp>)
Advanced intelligence is required for the
sophisticated behavior of the advanced robots such as service
robots, assistive robots, etc. In this session, the latest learning
methods of intelligent behavior of robots are discussed. The
required intelligence for the certain kinds of the advanced robots
is also discussed in this session. Topics for contributions include,
but may not be limited, the following researches:
- Behavior Learning
- Sophisticated Behaviors of Robots
- Service Robots
- Human-support Systems
- Assistive Robots
- Behavior-based Intelligence
#3. Intelligent learning algorithms for
multi-robot systems
Daisuke Kitakoshi (Tokyo National College of
Technology, Japan,
A variety of learning algorithms has been proposed
and researched over the past few decades. This session focuses on
intelligent learning algorithms for multi-robot to acquire an
appropriate behavior in their own environments. Research papers in
the algorithms for agents behaving in virtual environments and those
for multi-robot and multi-agent systems are also welcome. Topics for
contributions include, but may not be limited, the following
researches:
- Multi-robot Learning
- Multi-agent Learning
- Reinforcement Learning
- Learning Algorithms
- Cooperative Behaviors
- Swarm Robotics
- Collective Intelligence
Please forward your special session proposals to Workshop Co-Chairs.
Honghai Liu, University of Portsmouth, UK
Naoyuki Kubota, Tokyo Metropolitan University, Japan
For program inquiries, contact RiiSS 2013 Program Co-chairs: Honghai Liu (University of Portsmouth, UK) at Honghai.Liu+port.ac.uk and/or Naoyuki Kubota (Tokyo Metropolitan University, Japan) at kubota+tmu.ac.jp (change "+" into "@").
- Valentina Balas, University of Arad, Romania
- Janos Botzheim, Tokyo Metropolitan University, Japan
- Jiangtao Cao, Liaoning Shihua University, China
- Chee Seng Chan, University of Malaya, Malaysia
- Ryad Chellali, Institute of Italy Technologies, Italy
- Xiang Chen, University of Windsor, Canada
- Zhaopeng Chen, German Aerospace Center, Germany
- Sung-Bae Cho, Yonsei University, Korea
- Samir Garbaya, ENSAM - Arts et Metiers ParisTech, France
- Dongbing Gu, University of Essex, UK
- Frank Guerin, University of Aberdeen, UK
- Maki Habib, The American University in Cairo, Egypt
- Donggui Han, Wuhan Textile University, China
- Mehdi Khoury, University of Southampton, UK
- Robert Kozma, University of Memphis, USA
- Daisuke Kurabayashi, Tokyo Institute of Technology, Japan
- Hak-Keung Lam, King's College London, UK
- Hongyi Li, Portsmouth University, UK
- Xinde Li, Southeast University, China
- Qiinggang Meng, Loughborough University, UK
- Gyula Mester, University of Szeged, Hungary
- Kazuhiro Ohkura, Hiroshima University, Japan
- Gaoxiang Ouyang, Beijing Normal University, China
- Gary Parker, Connecticut College, USA
- Nicolas Pugeault, University of Surrey, UK
- Imre Rudas, Obuda University, Hungary
- Ulrich Ruckert, University of Paderborn, Germany
- Kave Salamatian, University of Savoie, France
- Joaquin Sitte, Queensland University of Technology,
Australia
- Indra Adji Sulistijono, EE Polytechnic Institute of
Surabaya, Indonesia
- Jiacheng Tan, Portsmouth University, UK
- Jozsef Tar, Obuda University, Hungary
- Kok Wai Wong, Murdoch University, Australia
- Peter Xu, University of Auckland, New Zealand
- Hao Ying, University of Wayne, USA
- Xuguang Zhang, Yanshan University, China
- Junyang Zhao, Xi'an Research Inst. of Hi-tech, China