This article describes a method for building a cognitive map of a virtual urban environment. Our routines enable virtual humans to map their environment using a realistic model of perception. We based our implementation on a computational framework proposed by Yeap and Jefferies (1999) for representing a local environment as a structure called an absolute space representation (ASR). Their algorithms compute and update ASRs from a 2-1/2-dimensional (2-1/2D) sketch of the local environment and then connect the ASRs together to form a raw cognitive map. Our work extends the framework developed by Yeap and Jefferies in three important ways.

A learning problem is referred to as classification if its output take discrete values in a set of possible categories and regression if it has continuous real-valued output. A simple and useful model of an input-output functional relationship is to assume that the output variable can be expressed approximately as a linear combination of its input vector components. These linear models include the linear least squares method for regression and the logistic regression method for classification. Because a linear model has limited prediction power by itself, there has been extensive research in nonlinear models such as neural networks. However, there are two major problems with the use of nonlinear models: First, they are theoretically difficult to analyze, and second, they are computationally difficult to solve.

The services and benefits that clients receive are based largely on such reviews and assessments. The failure to perform accurate reviews and assessments in a timely manner can result in a client being denied access to services when they most need them. The typical scenario with regard to case review and assessment in social services situations involves a professional caseworker reviewing a client's file, conducting a phone or in-person interview if necessary, and making an assessment using the information obtained from the review and heuristics developed from experience. The caseworker is generally a professional who possesses expertise in the appropriate field. Some examples of fields where this expertise is found include medicine, mental health, and education.

Its multiple functions-- including grammar-based gap-filling exercises, scenario show, free chatting, and chatting on a given topic--can satisfy the various requirements for students with different backgrounds and learning abilities. After a brief explanation of the conception of the dialogue system, as well as a survey of related works, I will illustrate the system structure and describe its pedagogical functions with the underlying AI techniques, such as natural language processing and rulebased reasoning, in detail. I will summarize the free Internet usage within a six-month period and its integration into English classes in universities and middle schools. The evaluation findings about the class integration show that the chatting function has been improved and frequently utilized by users, and the application of the CSIEC system on English instruction can motivate learners to practice English and enhance their learning process. Finally, I will conclude with potential improvements.

De Groot was going on a year long trip to the U.S. and the highlight of his journey was a visit to Herb Simon and Allen Newell. I met Allen for the first time when I came for a two semester long visit to Carnegie Mellon University in 1968. This encounter was a distinct factor in my later decision to join the faculty at Carnegie Mellon University. I interacted with Allen much more closely when I became department head in 1979. He was for me a mentor and a sounding board for ideas I wanted to pursue for computer science at Carnegie Mellon University. I enjoyed working with many good friends on the faculty, but Allen was really special. Many of us will remember him for his evenhanded treatment of all students at the Black Friday meetings. He would never pursue his own agenda, he would always look for the merit of a student's work and not whether the rules were violated. He was a staunch defender of the rule that replaces all rules, which says that the only thing that counts is whether or ...

Although AI Topics is designed for the lay public, it serves a much larger audience. Much of the genetic code for this web site, however, was actually written when the American Association for Artificial Intelligence (AAAI) came into existence. In the 1980 President's Message delivered by AAAI's first president, Allen Newell, one finds many of the responsibilities, principles, and protocols that have become part of the very fiber of AAAI. Not surprisingly, some of these elements were inherited (Newell 1980, p. 3): [W]e are a society born into a community of societies. Scientific societies are for their science.

"With the summer camp season fast approaching, kids across the country will be stocking up on hiking shoes, bug spray and other necessities for adventures in the great outdoors. Thousands of others, however, will be enjoying adventures of the indoor variety: creating video games, building robots and designing Web pages. Computer camp, as it was known to an earlier generation, just isn't what it used to be. With the booming growth of video games, the Internet and digital media, technology-minded kids have an enormous variety of things to learn at technology camps, which are often taught on the campuses of major universities.... Camp administrators say enrollment is up from last year.... And while the kids are on the computers for five to six hours a day, the instructors also take them outside for activities to break up the day."

This book looks at some of the results of this synergy among AI, cognitive science, and education. Examples include virtual students whose misconceptions force students to reflect on their own knowledge, intelligent tutoring systems, and speech recognition technology that helps students learn to read. Some of the systems described are already used in classrooms and have been evaluated; a few are still laboratory efforts. The book also addresses cultural and political issues involved in the deployment of new educational technologies. ISBN 0-0-262-56141-7 To order call 800-405-1619.

This article focuses on contributions that AI can make to address longterm educational goals. Challenges are described that support: (1) mentors for every learner; (2) learning 21st century skills; (3) interaction data for learning; (4) universal access to global classrooms; and (5) lifelong and lifewide learning. A vision and brief research agenda are described for each challenge along with goals that lead to development of global educational resources and the reuse and sharing of digital educational resources. Instructional systems with AI technology are described that currently support richer experiences for learners and supply researchers with new opportunities to analyze vast data sets of instructional behavior from big databases that record elements of learning, affect, motivation, and social interaction. Personalized learning is described that facilitates student and group experience, reflection, and assessment.

An Artist at RPI Who Draws on the Future--Graduate student in electronic arts uses provocative acts to make people think about issues. "Last February, Boryana Rossa and her colleagues sent a decree of robot rights by email to the Pope's people at the Vatican. It should be considered a sin, the decree said, to kill an artificially created, sentient being (that is, a robot). Robots have the right to chose their own religion, it continued. An entity or creature created by humans must be considered equal to humans.