Improving Knowledge Handling by Building Intelligent Systems Using Social Agent Modelling

Any purposeful organization can be understood as a value network. The main goal of this network is to deliver the highest value from the interdependencies between nodes. Improvement in this domain requires to increase efficiency, response time, knowledge availability and knowledge storing. One of the most interesting research topics in the field of multi-agent systems is the definition of models with the aim of representing social structures such as organizations and coalitions, to control the emergent behaviour of open systems. This paper presents an approach to capture knowledge from social environment by building new features in the social network analysis systems and use this knowledge as a source for modelling multi-agent systems. This paper presents a different approach to capture knowledge from social environment and handle social aspects in intelligent analysis systems by developing and simulating agentpsilas behaviour. Those proposed methods will help to represent knowledge in a new way as well as simulate and automate knowledge flow.