AGADE using personal preferences and world knowledge to model agent behaviour

Abstract

BDI agents provide a common well established approach for building multi-agent simulations. In this paper we demonstrate how semantic technologies can be used to model agent behaviour. Beliefs, desires and intentions are mapped flexibly to corresponding OWL ontologies structured in layers. This reduces Java coding efforts significantly. Reasoning mechanisms and rule evaluation are used to compute agent behaviour by deriving an agent's actions from declaratively formulated rules. An agent's knowledge of its environment and its personal preferences can be expressed and human behaviour can be simulated. The approach is implemented in an integrated tool for running round based agent simulations (AGADE).