Sweetening Regulated Open Multi-Agent Systems with Support for Agents to Reason about Laws

Inspired by the Tim Berners-Lee’s vision of a Semantic Web, this work aims to present an approach to regulate open Multi-Agent Systems (MAS) based on ontologies plus layers of logic and rules for data inference. In our approach, a top-down modeling of laws is designed for regulating an open MAS. We propose to regulate agents’ actions based on four levels of abstractions: Environment laws, organization laws, role laws and interaction laws. These levels of regulations are represented by a domain independent normative ontology, which has the six related main concepts: Environment, Organization, Role, Action, Norm and Penalty. The layer of logic from our solution is composed of a combination of Description Logic, Deontic Logic and some ideas from Defeasible Logic. The rule layer is composed of user defined rules and a rule-based inference engine. Some advantages of this work are: automatic composition of laws by using rules and inference, facility to regulate agents’ actions considering all the designed law levels, consistency check for pre-defined laws, and support for blackboxes agents to reason about laws in open MAS.