Real-time problem solving is not only reasoning about time, it is also reasoning in time. This ability is becoming increasingly critical in systems that monitor and control complex processes in semiautonomous, ill-structured, real-world environments. Many techniques, mostly ad hoc, have been developed in both the real-time community and the AI community for solving problems within time constraints. However, a coherent, holistic picture does not exist. This article is an attempt to step back from the details and examine the entire issue of real-time problem solving from first principles. We examine the degrees of freedom available in structuring the problem space and the search process to reduce problem-solving variations and produce satisficing solutions within the time available. This structured approach aids in understanding and sorting out the relevance and utility of different real-time problem-solving techniques.

The Fifth International Conference on Genetic Algorithms was held at the University of Illinois at Urbana-Champaign from 17-21 July 1993. Approximately 350 participants attended the multitrack conference, which covered a wide range of topics, including genetic operators, mathematical analysis of genetic algorithms, parallel genetic algorithms, classifier systems, and genetic programming. This article highlights the major themes of the conference by discussing a few papers in detail.

The Hong Kong-based Mass Transit Railway Corp. (MTRC) has developed the Station Management Expert e Norwegian Police Data Center help predict aircraft fires and other System (SMES). SMES is an intelligent utilized an expert system to catastrophes. The police put and risk factors from the records functions and advising the controller the intelligent application online to of the National Transportation Safety of actions to take in case of emergency. The system is installed in Ya Ma at the games while complying with Carnegie Group and Westinghouse Tei Station as a test site, and the complex national employment regulations. Electric (both in Pittsburgh, Penn.) are MTRC plans to expand its use Plans are to deploy and network working with Pittsburgh area medical throughout the subway system as it the expert system into every law centers to develop an intelligent proves to be successful. The network Martin Marietta (Bethesda, Md.) is developed a neural network application will gather and organize data on using a real-time expert system to that has improved the efficiency clinical diagnoses, treatment, clinical build the Traffic Operations Center of its direct mail marketing efforts by and research findings, and patient (TOC) component of its Intelligent 35%.

The human orientation system is a complex system in which the brain merges information from a variety of sensors to help maintain a coherent interpretation of body position and movement. These sensors include the semicircular canals and the otolith organs located in the inner ear as well as vision and somatosensory perception. I designed a model of this system based on the observer theory model (OTM), which was developed by Merfeld (1990) for the orientation system of the squirrel monkey. Under this scheme, the central nervous system has an internal representation of the sensor organs and tries to minimize the error between its estimate of the sensory afferent signals and the actual afferent signals. As designed, MARIKA's goal is to classify the vestibular system of the subject as normal or abnormal and propose a corresponding model. It works iteratively until the results of the proposed experiment can be modeled. Additional experiments can be presented in succession to the same model.

Recent general AI conferences show a decline in both the number and the quality of vision papers, but there is tremendous growth in, and specialization of, computer vision conferences. Hence, one might conclude that computer vision is parting or has parted company with AI. This article proposes that the divorce of computer vision and AI suggested here is actually an open marriage: Although computer vision is developing through its own research agenda, there are many shared areas of interest, and many of the key goals, assumptions, and characteristics of computer vision are also clearly found in AI.

Immediately preceding the 1993 National Conference on Artificial Intelligence (NCAI) in Washington D.C., a new conference series on the application of AI to molecular biology was inaugurated in neighboring Bethesda, Maryland. The First International Conference on Intelligent Systems for Molecular Biology (ISMB-93), held 6-9 July 1993 at the Lister Hill Center of the National Library of Medicine (NLM), attracted over 200 computer scientists and biologists from 13 countries.

The Second Annual Robotics Competition and Exhibition was held in July 1993 in conjunction with the National Conference on Artificial Intelligence. This article reports some of my experiences in helping to design and run the contest and some reflections, drawn from post mortem abstracts written by the competitors, on the relation of the contest to current research efforts in mobile robotics.

The Association for the Advancement of Artificial Intelligence sponsored a number of workshops in conjunction with the Eleventh National Conference on Artificial Intelligence held 11-15 July 1993 in Washington, D.C. This article contains reports of four of the workshops that were conducted: AI Models for System Engineering, Case-Based Reasoning, Reasoning about Function, and Validation and Verification of Knowledge Based Systems.

To integrate robotics into society, it is first necessary to measure and analyze current societal responses to areas within robotics. This article is the second in a continuing series of reports on the societal effects of various aspects of robotics. In my previous article, I discussed the problems of sensor abuse and outlined a program of treatment. However, despite the wide dissemination of that article, there are still numerous empty beds at the Susan Calvin Clinic for the Prevention of Sensor Abuse. Sensor abuse continues unabated despite strong evidence that there is a better way. In this article, I explore the age-old question, Why does the robotics community look down on efficient sensing systems?

A simulated (Houston, Tex.) has selected Telepresence technology allows scientists The Consolidated Communications from the Advanced Technology Program signed a strategic alliance agreement Facility's Element Manager at the National Institute of Standards with Gensym (Cambridge, Mass.) to will allow data communications and Technology. The grant will use Gensym's G2 real-time expert system system operators to remotely configure, support Kurzweil AI's development of development tool. Chevron control and monitor the operation a spoken-language interface capable installations are using G2 to intelligently of the front-end processor, providing of controlling PC software applications monitor energy management simultaneous support for through natural language and process simulation in conjunction multiple manned space flight missions, instruction in combination with a with other systems. Logica Cambridge (Cambridge, Developers at Georgia Tech AT&T Universal Card Services England) is developing a virtual reality (Atlanta, Ga.) have designed a neural (Jacksonville, Fla.) has signed a multiyear application to improve presentation network modeling, control and diagnostic agreement with HNC (San Diego, of data for air traffic controllers. Falcon uses see the heights of different aircraft, linked to sensors and other data neural network technology to learn rather than just the altitudes displayed sources on the factory floor, the neural and identify unusual transaction pat-numerically.