An information agent is viewed as a deductive database consisting of 3 parts: an observation database containing the facts the agent has observed or sensed from its surrounding environment, an input database containing the information the agent has obtained from other agents, and an intensional database which is a set of rules for computing derived information from the information stored in the observation and input databases. Stabilization of a system of information agents represents a capability of the agents to eventually get correct information about their surrounding despite unpredictable environment changes and the incapability of many agents to sense such changes causing them to have temporary incorrect information. We argue that the stabilization of a system of cooperative information agents could be understood as the convergence of the behavior of the whole system toward the behavior of a "superagent", who has the sensing and computing capabilities of all agents combined. We show that unfortunately, stabilization is not guaranteed in general, even if the agents are fully cooperative and do not hide any information from each other. We give sufficient conditions for stabilization and discuss the consequences of our results.
In this paper communications for agents are based on push-technologies. It is interesting to see how the results could be extended to multiagent systems whose communication is based on pull-technologies ( @cite_10 , @cite_9 ).
@cite_9 @cite_10
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With the ever growing usage of the world wide IT networks, agent technologies and multiagent systems (MAS) are attracting more and more attention. Multiagent systems are designed to be open systems, wheras agent technologies aim at the design of agents that perform well in environments that are not necessarily well-structured and benevolent. Emergent system behaviour is one of the most interesting phenomena one can investigate in MAS. However, there is more to MAS design than the interaction between a number of agents. For an effective system behaviour we need structure and organisation. This paper presents basic concepts of a theory for holonic multiagent systems with the aim to define the building blocks of a theory that can explain organisation and dynamic reorganisation in MAS. In doing so it tries to bridge the well-known micro-macro gap in MAS theories. The basic concepts are illustrated with three application scenarios: flexible manufacturing, order dispatching in haulage companies, and train coupling and sharing. Several methodologies are supplied to multiagent system designers to help them defining their agents and their multiagent systems. These methodologies focus mainly on agents and on multiagent systems and barely consider how to design interaction protocols. A problem could emerge of this lack since interaction protocols are more and more complex. The aim of this article is to present our proposal of interaction protocol engineering which is based on the communication protocol engineering [10]. Interaction protocol engineering allows designers to define protocols from scratch. Our proposal is composed of five stages: analysis, formal description, validation, protocol synthesis and conformance testing.