This paper describes a mobile information access system based on a multi-agent architecture. With the rapid progress of wireless data communications, mobile Internet access will be more and more popular. In mobile environments, user location plays an important role for information filtering and flexible communication service. In this paper, we propose a mobile information service system where a user with a handy terminal accesses Internet in an open air to look up map information and related town information. Each user information is managed by an independent agent process. And the agent provides each user with a personal service collaborating with other applications. A map-based information service example based on this architecture is also described.

This paper describes the application of a neural network to the optimal routing problem in broadband multimedia networks, where the objective is to maximize network utilization while considering the performance required for each call. In a multimedia environment, the performance required for each call is different, and an optimal path must be found whenever a call arrives. A neural network is appropriate for the computation of an optimal path, as it provides real-time solutions to difficult optimization problems. We formulated optimal routing based on the Hop field neural network model, and evaluated the basic behavior of neural networks. This evaluation confirmed the validity of the neural network formulation, which has a small computation time even if there are many nodes. This characteristic is especially suitable for a large-scale system. In addition, we performed a computer simulation of the proposed routing scheme and compared it with conventional alternate routing schemes. The results show the benefit of neural networks for the routing problem, as our scheme always balances the network load and attains high network utilization.