Summer calendar of AI-related events.

To a forum for Ph.D. students to discuss Many of you have been receiving the evaluate submitted proposals more effectively, research and career interests.

Chapter 7 investigates how learning interest or relevance to them. Chapter 3 describes several techniques and evolution can interact to produce There appears to be no need to read for evolving autonomous robots adaptive individuals.

This article summarizes the results of the 6-7 July Workshop on Human Language Technology and Knowledge Management held in Toulouse, France. It describes invited keynotes, presentations, and results of brainstorming sessions to create a technology road map for this important area. The group also articulated grand challenges in human language technology and solutions to these challenges that could benefit facilities for knowledge discovery, access, and exploitation.

In other words, we have the categories we do because they preserve existing similarities among objects and are therefore informative. According to Goodman, one researchers are adopting richer and must specify in what respect two objects categories? What is the role approaches. If two objects are similar only of similarity in categorization? Can we approaches address some because they are in the same category, of the shortcomings of previous approaches.

What are the central issues of CAMD by robots and animals? What does neuroscience tell us about mental development? What computational studies for mental development are needed in neuroscience and psychology? How does a robot chine learning have fruitfully been develop its cognitive and behavioral the budding research area that informed by models of human learning. For example, developmental differ fundamentally from human real physical environment.

The Association for the Advancement of Artificial Intelligence held its 2001 Fall Symposium Series November 2-4, 2001 at the Sea Crest Conference Center in North Falmouth, Massachusetts. The topics of the five symposia in the 2001 Fall Symposia Series were (1) Anchoring Symbols to Sensor Data in Single and Multiple Robot Systems, (2) Emotional and Intelligent II: The Tangled Knot of Social Cognition, (3) Intent Inference for Collaborative Tasks, (4) Negotiation Methods for Autonomous Cooperative Systems, and (5) Using Uncertainty within Computation. This article contains brief reports of those five symposia.

CARMA is an advisory system for rangeland grasshopper infestations that demonstrates how AI technology can deliver expert advice to compensate for cutbacks in public services. CARMA uses two knowledge sources for the key task of predicting forage consumption by grasshoppers: (1) cases obtained by asking a group of experts to solve representative hypothetical problems and (2) a numeric model of rangeland ecosystems. These knowledge sources are integrated through the technique of model-based adaptation, in which case-based reasoning is used to find an approximate solution, and the model is used to adapt this approximate solution into a more precise solution. CARMA has been used in Wyoming counties since 1996. The combination of a simple interface, flexible control strategy, and integration of multiple knowledge sources makes CARMA accessible to inexperienced users and capable of producing advice comparable to that produced by human experts. Moreover, because CARMA embodies diverse forms of expertise, it has been used in ways that its developers did not anticipate, including pest management research, development of industry strategies, and in-state and federal pest-management policy decisions.

With the emergence of electronic-commerce systems, successful information access on electroniccommerce web sites becomes essential. Menu-driven navigation and keyword search currently provided by most commercial sites have considerable limitations because they tend to overwhelm and frustrate users with lengthy, rigid, and ineffective interactions. To provide an efficient solution for information access, we have built the NATURAL language ASSISTANT (NLA), a web-based natural language dialog system to help users find relevant products on electronic-commerce sites. The system brings together technologies in natural language processing and human-computer interaction to create a faster and more intuitive way of interacting with web sites. By combining statistical parsing techniques with traditional AI rule-based technology, we have created a dialog system that accommodates both customer needs and business requirements. The system is currently embedded in an application for recommending laptops and was deployed as a pilot on IBM's web site.

Because of military drawdowns and the need for additional transportation lift requirements, the United States Marine Corps developed a concept that enabled it to modify a commercial container ship to support deployed aviation units. However, a problem soon emerged in that there were too few people who were expert enough to do the unique type of planning required for this ship. Additionally, once someone did develop some expertise, it was time for him/her to move on, retire, or leave active duty. There needed to be a way to capture this knowledge. This condition was the impetus for the T-AVB AUTOMATED LOAD-PLANNING SYSTEM (TALPS) effort. TALPS is now a fielded, certified application for Marine Corps aviation.