HIVE-BDI: EXTENDING JASON WITH SHARED BELIEFS AND STIGMERGY

Abstract

The classic BDI model focuses on the internal functioning of a single-agent architecture. Neither shared beliefs nor spontaneous and indirect coordination via the environment are supported. We describe Hive-BDI, an extension of the Jason BDI-style language with shared beliefs implemented via the logic-based coordination language ReSpecT and with stigmergy obtained via digital pheromones. A case study where robots roaming an unknown environment collaborate for creating a map demonstrates the feasibility of our approach.