With the integration of multidisciplinary technologies of wireless communications, smart sensors and precise actuators under advancing statistical information fusion, we envisage the emergence of a new multi mobile robotic system (MMRS) paradigm to prompt a new family of superior applications.  In order to achieve this challenging goal we need to move away from the existing traditional approach towards an improved ‘intelligent robotic industry’ for which we require superior autonomous robots equipped with a well-defined degree of intelligence to manipulate collective information to manage their own local tasks as well as joining in with all agreed cooperative scenario-based objectives. Following a brief introduction to distributed intelligence, this keynote redefines ‘robotic intelligence’ and expands on ‘distributed intelligent robotic systems’ (DIRS), addressing their impact on the usefulness of MMRS applications and their influence in the future of the global, industrialised economy. For MMRS industrial performance we address some innovative deployment approaches where the benefits of platform technology are discussed for flexibility and performance. Comparing different approaches we examine the most desirable required platforms optimised for design, manufacturing, service and operational performance. We also look into the key technologies enabling the promised MMRS application paradigm. In some detail we examine some of the recent development programs to analyse and highlight sustainable intelligent development platforms and classify them for their degree of intelligence and their suitability for short and long term application scenarios. At the intelligence adoption level, we discus the way DIRS can be integrated to identify five levels of robot autonomy and self-management, cluster level for local cooperative objectives, scenario-based cooperative objectives, overlay system management and industrial management of technology (mot).

The knowledge service platform is considered as one of key technologies in moving toward knowledge society from information society. In this talk, he will focus on issues in the nature of knowledge as the target resources of this platform. There are two different types of knowledge, ‘by description’ and ‘by acquaintance’. He will call the former as knowledge information’ and the latter as ‘live knowledge’. ‘Live knowledge’ is found from domain experts when they solve a problem or make a decision for a specific situation. ‘knowledge information’ is usually generated by human experts who has ‘live knowledge’ when they are asked to explain how they solve problems. 

‘Knowledge’ in most knowledge service platforms is ‘knowledge information’ and some systems have a human network function like ‘Q&A’ to share ‘live knowledge’. The research and development for knowledge service platforms have focused on managing ‘knowledge information’ since the introduction of knowledge management systems later 1990s and people do not realize yet that this is a major cause of failures in most KMS systems in industries. In knowledge society, without the solution for ‘live knowledge’, the knowledge service systems only can provide ‘knowledge information’ and the future of knowledge service systems is not very bright. 

In this talk, he will review some of AI technologies and their strength and weakness to be used as a tool for ‘live knowledge’ for knowledge service platforms. Also he will review the relationship between two different types of knowledge and how they should be balanced.