Problem-solving techniques such as modeling, simulation, optimization, and network analysis have been used extensively to help agricultural scientists and practitioners understand and control biological systems. By their nature, most of these systems are difficult to quantitatively define. Many of the models and simulations that have been developed lack a user interface which enables people other than the developer to use them. As a result, several scientists are integrating knowledge-based- system (KBS) technology with conventional problem-solving techniques to increase the robustness and usability of their systems. To investigate the similarities and differences of leading scientists' approaches, a pioneer workshop, supported by the Association for the Advancement of Artificial Intelligence (AAAI) and the Knowledge Systems Area of the American Society of Agricultural Engineers, was held in San Antonio, Texas, on 10-12 August 1988. Part of the AAAI Applied Workshop Series, the meeting was intended to bring together researchers and practitioners active in applying AI concepts to agricultural problems.

The authors of this book, Edward A. Feigenbaum, Pamela McCorduck, and H. Penny Nii, have given us an absorbing collection of tales about the successful integration of expert systems into mainstream industry.

Giving Is Hard: The Complexity of Linear Navigation and Xiaofeng Chen, Wright State University, 274 SC9j22, Santa Clara, CA 95052.

Artificial Intelligence is solving more and more real world problems, but penetration into the complexities of government administration has been minimal. The author suggests that combining expert system technology with conventional procedural computer systems can lead to substantial efficiencies. Business rules can be removed from business-oriented computer systems and stored in a separate but integrated knowledge base, where maintenance will be centralized. Fourteen specific practical applications are suggested.

Hutchins not only presents machine translation research (such as problems of machine translation It is the theories, algorithms, and designs practical versus theoretical, empirical also not clear that the AI philosophy but also the history, goals, assumptions, versus perfectionist, and direct versus of understanding and meaning (p 327) and constraints of each project.

In response to this by Denker with an impressive series need, Shelby Lyman, the host of past of moves that ended in a sacrifice Public Broadcasting Station (PBS) which brought home the win. Everyone series on world chess championship seemed impressed with Hitech's matches, organized the AGS Challenge performance throughout the match, Match at the New School for although it was clear the audience Social Research in New York City. Denker Funding for this event was provided was generous in his praise of Hitech, by AGS Computers, Inc., a New Jersey-based saying, "The machine gave me a real software firm. The match trimming; I am very impressed." The was held September 22-25, with one final game of the match follows with game played each day, and was widely a few annotations.

CMU's staff has developed an email for submissions and ways of promoting interface that will be available for Library $85

At their meeting in Milan in 1987, IJCAI Inc. was faced with the issue of multiple submission of papers. IJCAI announces its current policy on this issue through this article. The trustees hope this announcement will encourage a debate from which a consensus can emerge.

The emergence of the blackboard architecture as a widely used paradigm for problem solving led us and other members of the blackboard research community to organize a workshop. The workshop was held during the 1987 Association for the Advancement of Artificial Intelligence Conference in Seattle. The main purpose of the workshop was to highlight the advances in blackboard architectures since the introduction of the paradigm in Hearsay-II and identify issues relevant to future blackboard system research. This article describes the issues raised and the discussions in each of the five workshop panels.

Hutchins not only presents machine translation research (such as problems of machine translation It is the theories, algorithms, and designs practical versus theoretical, empirical also not clear that the AI philosophy but also the history, goals, assumptions, versus perfectionist, and direct versus of understanding and meaning (p 327) and constraints of each project.