The integration of GRID and MAS (Multi-Agents Systems) is an active research topic. We have recently proposed the Agent-Grid Integration Language, to describe a service-based integration of GRID and MAS models. However, the complexity of the mutual integration aspects leads us to define a rigorous way to formalize the key concepts, their relations and the integration rules by means of an ontology. With this ontology, we can describe the elements and their composition that occur in various service exchange scenarios with agent on the Grid. The ontology could be used both to model the behaviour of GRID-MAS integrated systems and to check the consistency of these systems and their instances. A concrete scenario is illustrated.
This paper addresses the architectural foundations of dynamic workflows in distributed multi-agent systems (MAS) integrated in Grid context. The purpose is to design an architecture at the same time taking into consideration tasks dependencies among agents, adaptation with respect to historic lessons learnt from past behaviour (memory) and the autonomous decisions when an unpredicted event occurs. In order to do this, given one ontology, called AGIO, which describes Agent-Grid Integration, we propose a workflow based on MAS with a complementary decision-making aid using Markov Logic Networks (MLN).
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