Multi-agent recommendation system in Internet of Things

The Internet of Things (IoT) aims to bridge the gap between the physical and the cyber world to allow a deeper understanding of user preferences and behaviors. The interactions and relations between users and things need of an effective and efficient recommendation approaches to better meet users interests. Suggesting useful things in IoT environment is a very important task for many applications such as urban computing, smart cities, health care, etc., and it needs to be widely investigated. The goal of recommendation systems is to produce a set of significant suggestions for a user with given characteristics. In this paper, a multi-agent algorithm that, by exploiting of a decentralized and self organizing strategy, builds a distributed recommendation system in IoT environment, is proposed. Things are represented through bit vectors, the thing descriptors, obtained through a locality preserving hash function that maps similar things into similar bit vectors. Cyber agents manage the thing descriptors and exchange them on the basis of ad-hoc probability functions. The outcome is the emergence of an organized overlay-network of cyber agents that allows to obtain an efficient things recommender system. Preliminaries results confirm the validity of the approach.