Taking into account the importance of e‐commerce and the current applications of AI techniques in this area, this research aims to adequate the design of a multi‐agent system for the provisioning of e‐services in u‐commerce environments. This proposal is centred on the methods of evaluation in a u‐e‐commerce environment.
The multi‐agent systems (MAS) approach is based on an MAS model developed for AmI that has been redesigned to support u‐commerce. The use of a recommendation system, previously developed by the research group, is suggested for this MAS. The methodological proposal centres on the evaluation of this type of system.
The evaluation of this type of system is the principal problem of current research. Therefore, this is the main contribution of the paper.
The different evaluation methods that are proposed, whether qualitative or quantitative, offer the possibility of measuring the added value that the context can give to the use of e‐services in different domains of application. Qualitative evaluation should consider the customer as a central piece in the system. In addition, quantitative methods should objectively evaluate the contribution of context to the application.
At present, there is no single method for evaluating the benefits of different u‐commerce systems, so a new method needs to be found based on these techniques.
The research proposes an MAS designed for u‐commerce domains, analyzes the capacity of trust management techniques in this environment, and proposes several evaluation methods to show the benefits of context information in the use of e‐services. Several real developments are described to show the different applications of MAS in u‐commerce and how evaluation is carried out.
