Applying DB-transaction semantics to agent interactions

Abstract: Both artificial intelligence (AI) and database (DB) communities have advantages in incorporating features from each other's areas. From a DB view, handling of complexity in today's information systems can be aided by incorporating AI features, and database environments could gain in flexibility by entrusting some of their functionality to agent systems. Contemplated from the AI view, agent systems could gain in robustness by being based on DB-systems. By applying the semantics of database-transaction to interactions between agents in a multiagent-system, and analysing the consequences, this project endeavours to cross borders of the two research areas. In the project, states where drop-out of some agent is severe to the task fulfilment, of the system, have been identified, and examined after applying transaction semantics to the agent interactions. An existing system for multiagent applications, JADE, has been examined in order to investigate how problem situations are handled in practice. The result from this work shows the feasibility to contemplate both type of systems as very similar, but modelled and viewed in different ways.