The fundamental observation we will hands ask, have all the big ideas gone? This is, put field is a real change with several causes, differently, a traditional thesis of artificial and not simply an illusion. Two factors intelligence, namely that the immediately spring to mind: hardware may vary but the basic problems of intelligent action remain the - To some extent, it reflects the maturation same. For example, one big problem is of the field. This notion permeates all of problems are solved, the remaining of artificial intelligence's relatives but problems are harder, making progress less so artificial intelligence itself.

This book is a collection of research papers covering a range of topics in expert systems and knowledge engineering.

We propose an approach for meeting real-time constraints in AI systems that views (1) time as a resource that should be considered when making control decisions, (2) plans as ways of expressing control decisions, and (3) approximate processing as a way of satisfying time constraints that cannot be achieved through normal processing. In this approach, a real-time problem solver estimates the time required to generate solutions and their quality. This estimate permits the system to anticipate whether the current objectives will be met in time. The system can then take corrective actions and form lower-quality solutions within the time constraints. These actions can involve modifying existing plans or forming radically different plans that utilize only rough data characteristics and approximate knowledge to achieve a desired speedup. A decision about how to change processing should be situation dependent, based on the current state of processing and the domain-dependent solution criteria. We present preliminary experiments that show how approximate processing helps a vehicle-monitoring problem solver meet deadlines and outline a framework for flexibly meeting real-time constraints.

This is Part 1 of a two-part article. Part 2 covers tort liability and computers as expert witnesses. It will appear in the Summer 1988 issue of AI Magazine. Technological developments that remove ever-increasing numbers of cognitive tasks from human control will alter the assumptions on which current legal rules are based. These rules will have a growing impact on AI researchers and entrepreneurs as their work reaches a growing audience of beneficiaries. In order to accommodate the needs of practitioners and their recipients, courts and lawmakers will be forced to reevaluate principles whose foundations were developed well before the implications of advanced technology could have been predicted. This article attempts to identify areas of law in which the need for accommodation will be greatest and provide some insight into the process and the direction of change.

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In Proceedings of the Fifth International Conference on Machine Learning, pages 54-64, Ann Arbor, Michigan.

In this proposal, I describe a. method for formulating plans from

Proceedings of the Seventh National Conference on Artificial Intelligence: 301-306

Proceedings of the National Conference on Artificial Intelligence, 245-250

Proc. AAAI-88, Vol. 2, pp. 607–611