In open normative multi-agent communities, an agent is not usually and explicitly given the norms of the host agents. Thus, when it is not able to adapt the communities’s norms, it is totally deprived of accessing resources and services from the host. Such circumstance severely affects its performance resulting in failure to achieve its goal. Consequently, this study attempts to overcome this deficiency by proposing a technique that enables an agent to detect the host’s potential norms via self-enforcement and update its norms even in the absence of sanctions from a third-party. The authors called this technique as the potential norms detection technique (PNDT). The PNDT consists of five components: Agent’s belief base; observation process; potential norms mining algorithm (PNMA); verification process; and updating process. The authors demonstrate the operation of the PNMA algorithm by testing it on a typical scenario and analyzing the results on several perspectives. The tests’ results show that the PNDT performs satisfactorily albeit the success rate depends on the environment variables settings.
All Science Journal Classification (ASJC) codes
- Computer Science (miscellaneous)
- Information Systems