CALoR: Context-Aware and Location Reputation model in AmI environments
Spatial conditions of observation are considerably important for some services. Existing distance between the requester and provider agents, while interacting, may influence in a significant way the quality of the provided services. In these cases, recommendations and direct evaluation of services have to take into account such distances. The contribution of this paper is the development of a reputation system that takes into account spatial and temporal properties of interactions for ambient intelligence environments. The system was defined as an extension of an already existing Protege ontology for Ambient Intelligence domains: suggested the corresponding equations (inspired in previous works from other authors): validated the proposal with a case of use, we implemented the corresponding behaviors of JADE agents: and executed simulations to show how considering distance may improve reputation accuracy in Ambient Intelligence domains.
ubiquitous computing trust models autonomous agents