HIS
Overview
Hybridization of intelligent systems is a promising research field of computational intelligence focusing on synergistic
combinations of multiple approaches to develop the next generation of intelligent systems. A fundamental stimulus to the
investigations of Hybrid Intelligent Systems (HIS) is the awareness that combined approaches will be necessary if the remaining
tough problems in artificial intelligence are to be solved. Neural computing, machine learning, fuzzy logic, evolutionary
algorithms, agent-based methods, among others, have been established and shown their strength and drawbacks. Recently, hybrid
intelligent systems are getting popular due to their capabilities in handling several real world complexities involving imprecision,
uncertainty and vagueness.
The objectives of the international meetings fused under the umbrella of the HIS conference series are to increase the awareness
of the research community of the broad spectrum of hybrid techniques, to bring together AI researchers from around the world to
present their cutting-edge results, to discuss the current trends in HIS research, to develop a collective vision of future
opportunities, to establish international collaborative opportunities, and as a result to advance the state of the art of the
field.
Steering Committee
Chairs:
Ajith Abraham, Chung-Ang University, Korea
Mario Koeppen, Fraunhofer IPK FHG, Germany
International Committee:
David Fogel, Natural Selection Inc., USA
Janusz Kacprzyk, Polish Academy of Sciences, Poland
Vasile Palade, University of Oxford, UK
David Corne, University of Exeter, UK
Takeshi Yamakawa, Kyushu Institute of Technology, Japan
Javier Ruiz-del-Solar, Universidad de Chile, Chile
Jae Oh, Syracuse University, USA
Marley Vellasco, PUC-Rio, Brazil
Antony Satyadas, IBM, USA
