A Bayes network based classifier for distinguishing terrestrial rocks from meteorites is implemented onboard the Nomad robot. Equipped with a camera, spectrometer and eddy current sensor, this robot searched the ice sheets of Antarctica and autonomously made the first robotic identification of a meteorite, in January 2000 at the Elephant Moraine. This paper discusses rock classification from a robotic platform, and describes the system onboard Nomad. 1 Introduction Figure 1: Human meteorite search with snowmobiles on the Antarctic ice sheets, and on foot in the moraines. Antarctica contains the most fertile meteorite hunting grounds on Earth. The pristine, dry and cold environment ensures that meteorites deposited there are preserved for long periods.

Several regular programs will return is March 15, 2002.

They express both thoughts and California (USC)/Information Sciences Institute emotions; emotional expression is important to (ISI) is to develop new technologies that portray characteristics of enthusiasm and empathy promote effective learning and increase learner that are important for human teachers. These technologies are intended They are knowledgeable about the subject matter to result in interactive learning materials that being learned, of pedagogical strategies, and support the learning process and that complement also have knowledge about how to find and and enhance existing technologies relevant obtain relevant knowledge from available to learning such as the World Wide Web. Our work draws significant inspiration from Figure 1 shows one of the guidebots that we human learning and teaching. We piece of equipment called a high-pressure air seek a better understanding of the characteristics compressor aboard United States Navy ships. As learners view instructional materials, guidebots can provide useful commentary on these materials.

Choosing an environment is an important decision for agent developers. A key issue in this decision is whether the environment will provide realistic problems for the agent to solve, in the sense that the problems are true to the issues that arise in addressing a particular research question. In addition to realism, other important issues include how tractable problems are that can be formulated in the environment, how easy agent performance can be measured, and whether the environment can be customized or extended for specific research questions. In the ideal environment, researchers can pose realistic but tractable problems to an agent, measure and evaluate its performance, and iteratively rework the environment to explore increasingly ambitious questions, all at a reasonable cost in time and effort. As might be expected, trade-offs dominate the suitability of an environment; however, we have found that the modern graphic user interface offers a good balance among these trade-offs. This article takes a brief tour of agent research in the user interface, showing how significant questions related to vision, planning, learning, cognition, and communication are currently being addressed.

The long-term future of space exploration at the National Aeronautics and Space Administration (NASA) is dependent on the full exploitation of autonomous and adaptive systems, but mission managers are worried about the reliability of these more intelligent systems. The main focus of the workshop was to address these worries; hence, we invited NASA engineers working on autonomous and adaptive systems and researchers interested in the verification and validation of software systems. The dual purpose of the meeting was to (1) make NASA engineers aware of the verification and validation techniques they could be using and (2) make the verification and validation community aware of the complexity of the systems NASA is developing. The workshop was held 5 to 7 December 2000 at the Asilomar Conference Center in Pacific Grove, California.

Shop is a hierarchical task network planning algorithm that is provably sound and complete across a large class of planning domains. It plans for tasks in the same order that they will later be executed, and thus, it knows the current world state at each step of the planning process. For example, shop's preconditions can include logical inferences, complex numeric computations, and calls to external programs.

C. Furniture, Fixtures and Equipment: Effective for 1996 the Association Furniture, fixtures and equipment are has changed its method of accounting stated at cost, less accumulated depreciation.

The Association for the Advancement of Artificial Intelligence presented the 2000 Fall Symposium Series was held on Friday through Sunday, 3 to 5 November, at the Sea Crest Oceanfront Conference Center. The titles of the five symposia were (1) Building Dialogue Systems for Tutorial Applications, (2) Learning How to Do Things, (3) Parallel Cognition for Embodied Agents, (4) Simulating Human Agents, and (5) Socially Intelligent Agents: The Human in the Loop.

The long-term future of space exploration at the National Aeronautics and Space Administration (NASA) is dependent on the full exploitation of autonomous and adaptive systems, but mission managers are worried about the reliability of these more intelligent systems. The main focus of the workshop was to address these worries; hence, we invited NASA engineers working on autonomous and adaptive systems and researchers interested in the verification and validation of software systems. The dual purpose of the meeting was to (1) make NASA engineers aware of the verification and validation techniques they could be using and (2) make the verification and validation community aware of the complexity of the systems NASA is developing. The workshop was held 5 to 7 December 2000 at the Asilomar Conference Center in Pacific Grove, California.

For more details, see Nau et al. 's preconditions can include logical inferences, 's preconditions two methods for traveling from one location can include Horn-clause inferencing, numeric to another: (1) traveling by airplane and (2) computations, and calls to external programs. 's expressive power can be used to create a totally ordered list of subtasks. Suppose domain representations for complex application that all these subtasks are primitive except for domains. For example, the Horn 4. if t is primitive (i.e., there is an operator for t) then clauses can include calls to attached procedures 5. nondeterministically choose an operator o for t We believe the primary 14. endif's higher level of expressivity made it possible to formulate highly expressive domain algorithms in's data structures to make them faster; for example, we found that a simple change to the data structure We intend to make more optimizations in the near future. (Aha and Breslow 1997).