Big incremental dynamic case-based reasoning-multi-agents system (BIDCBR-MAS) based on cloud computing
Abdelhamid Zouhair, El Mokhtar En-Naimi · 2016
In this paper we present our approach in the fields of Case-Based Reasoning (CBR), Big Data and Cloud computing. 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 related to real-time dynamic parameters (identify the different situations possible that need to be defined by the designer beforehand). Our approach based Big Data Multi-Agent System and Cloud Computing is able to study dynamic situations (recognition, prediction, and learning situations). We propose a generic approach able to learn automatically from them experiences in order to acquire the knowledge automatically. Based on the Case-Based Reasoning and multi-agent paradigm, we propose a modification of the static CBR cycle in order to introduce a dynamic process of Case-Based Reasoning based on a dynamic similarity measure able to evaluate in real time the similarity between a dynamic situation (target case) and past experiences stored in the memory (sources case) in order to predict the target case in the future.