By Manuel Kolp, Brian Henderson-Sellers, Haralambos Mouratidis, Alessandro Garcia, Aditya Ghose, Paolo Bresciani
This publication constitutes the completely refereed post-proceedings of the eighth foreign Bi-Conference Workshop on Agent-Oriented info structures, AOIS 2005, held in Hakodate, Japan, May9, 2006 and Luxembourg, Luxembourg, June 6, 2006.
The thirteen revised complete papers awarded have undergone rounds of reviewing and development and have been conscientiously chosen for inclusion within the e-book. The papers are prepared in topical sections on Modelling, Methodologies, Agent-oriented software program Engineering, and Applications.
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In Dellie Cuba, customers are obliged to make a down payment of 10% for every order placed to a seller. 2 Representing Our Created World The DynaCROM ontology was extended and instantiated, by using the Protégé Editor , for representing the world of our case study. As an example, the Environment (DynaCROM) concept was extended with the “Continent” and “Country” (domain) sub-concepts. Thus, “NorthAmerica”, “CentralAmerica”, and “SouthAmerica” were created as instances of the “Continent” concept; and “USA”, “Cuba” and “Brazil” were created as instances of the “Country” concept.
SCAAR uses this information as a precise updated input instead of using general and pre-defined (outdated) information. SCAAR keeps verifying norm compliance and, if a norm is violated, SCAAR sends that information to DynaCROM. 2 Using a Norm Enforcement Solution for Detecting Norm Violation For exemplifying how DynaCROM and SCAAR can represent a powerful complementary solution while detecting norm violation in open MASs, a simple (not completed) scenario is proposed. The scenario is created according to the world and norms from Section 3 and it can be summarized by the following steps: a.
Fig. 7. DynaCROM and SCAAR working together Providing Contextual Norm Information in Open Multi-Agent Systems 31 Fig. 7 illustrates how DynaCROM and SCAAR work together. DynaCROM is responsible for continuously informing SCAAR about the norms of agents, according to their current contexts. SCAAR uses this information as a precise updated input instead of using general and pre-defined (outdated) information. SCAAR keeps verifying norm compliance and, if a norm is violated, SCAAR sends that information to DynaCROM.