After a summary of the rules, we outline the high and low points of the competition. Devising a sweep pattern on a bounded established in past contests. The only wrinkle uncluttered surface to ensure complete coverage concerned bag capacity: if the robot encountered is a well-formed and solved problem. A domestic or small office venue offered Points were awarded for cleaning the messes more complexity. The areas were smaller and (or just moving over them) and making contained more furniture.

Researchers and technology developers from the National Aeronautics and Space Administration (NASA), other government agencies, academia, and industry recently met in Pasadena, California, to take stock of past and current work and future challenges in the application of AI to highly autonomous systems. The meeting was catalyzed by new opportunities in developing autonomous spacecraft for NASA and was in part a celebration of the fictional birth year of the HAL-9000 computer.

To remain competitive, enterprises must become increasingly agile and integrated across their functions. Enterprise models play a critical role in this integration, enabling better designs for enterprises, analysis of their performance, and management of their operations. This article motivates the need for enterprise models and introduces the concepts of generic and deductive enterprise models. It reviews research to date on enterprise modeling and considers in detail the Toronto virtual enterprise effort at the University of Toronto.

Details about program does not provide any scholarship information, please contact AAAI at these programs will also be mailed to funds, and is designed for local fss@aaai.org

Please send papers to: AAAI-99--American Association for Artificial Intelligence 445 Burgess Drive Menlo Park, CA 94025-3442 Registration and call clarification inquiries (only) may be sent to ncai@aaai.org.

Invited participants must 445 Burgess Drive, Menlo Park, CA register by September 9, and the final Registration materials for the Fifteenth 94025; by fax to 650-321-4457; or by registration deadline is September 23.

Lull's writings advanced the idea vert to Christianity because of a cognitive that non-mathematical reasoning can in artificial intelligence have defect. Some of appreciate the vast array of the combinations process, and that reasoning the most fundamental, surely, are that of God's or Christ's virtues. But does not proceed by syllogism, but by thinking is a computational process, Lull believed that infidels could be combinatorics. The decomposition can be made mechanical, and that the Further, he thought that a representation and recombination of attributes can be mathematics of computation involves of those combinations could represented by the decomposition and combinatorics. All of these ideas have be effectively presented by means of recombination of symbols, and that, as their origin, so far as we know, in the appropriate machines, and that was Lull's devices illustrate, is a process that work of an eccentric 13th century the key to his new method.

Interacting with a computer requires adopting some metaphor to guide our actions and expectations. Most human-computer interfaces can be classified according to two dominant metaphors: (1) agent and (2) environment. Interactions based on an agent metaphor treat the computer as an intermediary that responds to user requests. In the environment metaphor, a model of the task domain is presented for the user to interact with directly. The term agent has come to refer to the automation of aspects of human-computer interaction (HCI), such as anticipating commands or autonomously performing actions. Norman's 1984 model of HCI is introduced as reference to organize and evaluate research in human-agent interaction (HAI). A wide variety of heterogeneous research involving HAI is shown to reflect automation of one of the stages of action or evaluation within Norman's model. Improvements in HAI are expected to result from a more heterogeneous use of methods that target multiple stages simultaneously.

Buzzeo (Phoenix, Ariz.), a software engineering firm, has developed a highly adaptable self-service application that automates various administrative Bell Helicopter Textron (Fort Worth, rapid transit (BART) system. The lab functions for the higher-education Tex.), a manufacturer of helicopters, will develop a system to better train marketplace. This rule-based has implemented an intelligent system both new BART operators and those system has helped Buzzeo cut its to automate the procurement needing periodic retraining. ATS enables customers traffic problems at commercial airports. Technical Library at the to track packages through a The $9.3 million, two-story Phillips site on Kirtland Air Force Base, nationwide 800 number by simply building, called the Surface Development New Mexico, is using advanced pattern-recognition stating a tracking number to learn and Test Facility, is being built at technology to design the status of a package.

One of the most common mechanisms used for speeding up problem solvers is macro-learning. Macros are sequences of basic operators acquired during problem solving. Macros are used by the problem solver as if they were basic operators. The major problem that macro-learning presents is the vast number of macros that are available for acquisition. Macros increase the branching factor of the search space and can severely degrade problem-solving efficiency. To make macro learning useful, a program must be selective in acquiring and utilizing macros. This paper describes a general method for selective acquisition of macros. Solvable training problems are generated in increasing order of difficulty. The only macros acquired are those that take the problem solver out of a local minimum to a better state. The utility of the method is demonstrated in several domains, including the domain of NxN sliding-tile puzzles. After learning on small puzzles, the system is able to efficiently solve puzzles of any size.