Intelligent dynamic case-based reasoning using multi-agents system in adaptive e-service, e-commerce and e-learning systems

In this paper, we present our approach in the field of case-based reasoning (CBR). This approach is based on the reuse of previous traces that are similar to the current situation in a dynamic way. Several approaches have been used in this area, but they suffer from some limitations in automated real-time management dynamic parameters. We propose a generic approach multi-agent multi-layer able to learn automatically from their experiences. This approach involves (1) the use of incremental dynamic case-based reasoning (IDCBR) able to study dynamic situations (recognition, prediction and learning situations); (2) the use of multi-agents system and (3) the use of the user traces. When interacting with the platform such as e-service, e-learning, e-business and e-commerce, every user leaves his or her traces in the machine. The traces are stored in database, this operation enriches collective past experiences. Via monitoring, comparing and analysing these traces, the system keeps a constant intelligent watch on the platform.