AUTOCELL is a system developed to assist in the operation and management of cellular mobile networks operated by Singapore Telecom. Its deployment is in line with the company's strategic move to introduce intelligent software into its operations. With the help of AI concepts and techniques, the system has enhanced the operational efficiency and network capacity and increased customer satisfaction with the network.

The field of reinforcement learning has grown dramatically over the past several years, but with the exception of backgammon [8, 2], has had few successful applications to large-scale, practical tasks. This paper demonstrates that the practical task of routing packets through a communication network is a natural application for reinforcement learning algorithms.

We prove that except possibly for small exceptional sets, discretetime analogneural nets are globally observable, i.e. all their corrupted pseudo-orbitson computer simulations actually reflect the true dynamical behavior of the network. Locally finite discrete (boolean) neural networks are observable without exception.

We prove that except possibly for small exceptional sets, discretetime analog neural nets are globally observable, i.e. all their corrupted pseudo-orbits on computer simulations actually reflect the true dynamical behavior of the network. Locally finite discrete (boolean) neural networks are observable without exception.

"Q-routing" algorithm, related to certain distributed packet routing algorithms

MT Telecom, a Dutch telecommunications utility, has installed expert BNR Europe (Harlow, England), the instrument aboard the satellite. Pending system-based help desk systems to R&D subsidiary of telecommunications NASA approval, EUVE will be the centralize its 23 networked local data equipment supplier Northern first orbiting astrophysics mission to Telecom, is using virtual reality technology replace humans with AI technology. This installation proved to be a critical planning. The VR system allows Re:Member Data Services (Memphis, factor in helping the company BNR's engineers to visualize complex Tenn.), a data processor for obtain the IS0 9000 Total Quality installations and how they will work, credit union software services, has System Standard certification, a greatly saving time and effort compared automated all company service and requirement for those organizations to the traditional CAD system. Continental Bank (Chicago, Ill.) has expert system tracks all requests developed a client/server-based intelligent called in by users, and all requests Lockheed Missiles ST Space (Palo application to improve the can be accessed by anyone at the Alto, Calif.) has developed ASAP quality of its customer service.

These software between telephone, television, agents are on their way, and they're going to The be getting a lot of things accomplished by basic idea is that the networks that constitute interacting with each other. The question is, our telephone infrastructure, our television How will these agents be cooperating with (particularly cable) infrastructure, and our each other, competing with each other, and computer infrastructure will be coalescing into negotiating with each other? Now, the agents that we are interested in Another example is routing among looking at are heterogeneous, self-motivated telecommunication networks. The systems are not assumed to be packets, can pass over a network controlled by centrally designed. For example, if you have a one company onto another network controlled personal digital assistant, you might have one by another company, or it can pass that was built by IBM, but the next person through one country on through another. Computers that control a telecommunications They don't necessarily have a notion of global network might find it beneficial to enter into utility. Each personal digital assistant or agreements with other computers that control each agent operating from your machine is other networks about routing packets more interested in what your idea of utility is and efficiently from source to destination. The in how to further your notion of goodness. We're other agents ask them to do unless they have Another example is the proliferation of shared databases, where there's information They have sprung up with a vengeance in the last decade.

PROSE is a knowledge-based configurator platform for telecommunications products. Its outstanding feature is a product knowledge base written in C-classIC, a frame-based knowledge representation system in the KL-ONE family of languages. Unlike previous configurator applications, the PROSE knowledge base is in a purely declarative form that provides developers with the ability to add knowledge quickly and consistently. The PROSE architecture is general and is not tied to any specific telecommunications product.

PROSE is a knowledge-based configurator platform for telecommunications products. Its outstanding feature is a product knowledge base written in C-classIC, a frame-based knowledge representation system in the KL-ONE family of languages. It is one of the first successful products using a KL-ONE style language. Unlike previous configurator applications, the PROSE knowledge base is in a purely declarative form that provides developers with the ability to add knowledge quickly and consistently. The PROSE architecture is general and is not tied to any specific telecommunications product. As such, it is being reused to develop configurators for several different products. Finally, PROSE not only generates configurations from just a few high-level parameters, but it can also verify configurations produced manually by customers, engineers, or salespeople. The same product knowledge, encoded in C-classIC, supports both the generation and the verification of product configurations.

The application of neural networks to the demodulation of spread-spectrum signals in a multiple-access environment is considered. This study is motivated in large part by the fact that, in a multiuser system, the conventional (matched ter) fil receiver suffers severe performance degradation as the relative powers of the interfering signals become large (the "near-far" problem). Furthermore, the optimum receiver, which alleviates the near-far problem, is too complex to be of practical use. Receivers based on multi-layer perceptrons are considered as a simple and robust alternative to the optimum solution. The optimum receiver is used to benchmark the performance of the neural net receiver; in particular, it is proven to be instrumental in identifying the decision regions of the neural networks. The back-propagation algorithm and a modified version of it are used to train the neural net. An importance sampling technique is introduced to reduce the number of simulations necessary to evaluate the performance of neural nets.