Abstract. Agents that act as information brokers in large distributed systems (such as the internet) lower the cost of obtaining information. Agents have direct access to only a small part of such systems at any one time. This paper investigates the conditions in which agents successfully go through other agents in order to establish direct communication. A sumulated, large information market enables agents to acquire the information they seek if and only if market shares amoung broker agents conform to a power law distribution. This result, if it turns out to apply more generally, implies that agency theory based on utility maximisation does not provide any guidance to system properties. Thus certain aspects of the agent decision making process are implied by the properties of the system.
Abstract. In this paper we propose a methodology to help analyse tendencies in MAS to complement those of simple inspection, Monte Carlo and syntactic proof. We suggest an architecture that allows an exhaustive model-based search of possible system trajectories in significant fragments of a MAS using forward inference. The idea is to identify tendencies, especially emergent tendencies, by automating the search through possible parameterisations of the model and the choices made by the agents. Subsequently, a proof of these tendencies could be attempted over all possible conditions using syntactic proof procedures. Additionally, we propose a computational procedure to help implement this. The strategy consists of: unencapsulating the MAS so as to reveal the maximum information about logical dependencies in the system. This information is maximised by splitting the transition rules by time intervals and some parameters. An example applying this procedure is exhibited which 'compiles' the rules into this form. In the example the exploration of possibilities is speeded up by a factor of 14. This makes possible the complete exploration of model behaviour over a range of parameterisations and agent choices.
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