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Wasp: A Multi-agent System for Multiple Recommendations Problem

This paper proposed a multi-agent system using the social status of wasp to solve the problem of multiple simultaneous personalized recommendations (MSPRs). This problem occurs when several personalized campaigns are conducting simultaneously. The aim of this paper is two fold: i) to mimic the behavior of a wasp colony in nature for designing a robust bio-inspired algorithm and in the sequel strengthening the field of natural computing, and ii) using the collective intelligence of wasps to solve the NP-hard problem like multiple recommendations problem. The solution of MSPRs can be a new generation tool for recommendation system of e-commerce by replacing independent personalized recommendations.