The 2003 International Conference on Automated Planning and Scheduling (ICAPS-03) was held 9 to 13 June 2003 in Trento, Italy. It was chaired by Enrico Giunchiglia (University of Genova), Nicola Muscettola (NASA Ames), and Dana Nau (University of Maryland). Piergiorgio Bertoli and Marco Benedetti (both from ITC-IRST) were the local chair and the workshop-tutorial coordination chair, respectively. It is the result of merging two highly successful biennial conferences: (1) the International Conference on AI Planning and Scheduling (AIPS) and (2) the European Conference on Planning (ECP)--which alternately occurred beginning in 1991. The ICAPS-03 technical program took place from 11 to 13 June 2003.

This article presents the results of a multifaceted research and development effort that synergistically integrates AI research with military strategy research and practical deployment of agents into education. A distinguishing feature of this collaboration is the synergistic integration of AI research with military strategy research and the practical use of agents in education, as detailed in the following. View on the Evolution of the Software Development Process. strategic leaders at all the United States senior military service colleges, there is a great emphasis on the center of gravity analysis (Strange 1996). Hence, we have the third objective of this research, the educational objective of enhancing the educational process of senior military officers through the use of intelligent agent technology. Both programs emphasized the use of innovative challenge problems to focus and evaluate the research and development efforts.

The author acknowledges the kind cooperation of Professor Aravind Joshi, IJCAI program chairman, in extending the opportunity to produce this timely panel discussion The panelists included Dr Jack Williams. His presentation pinpointed the world forces of change, the government role in fostering efficient technological innovation, and the need to adapt to flexible manufacturing quickly. In discussing the AI industry, he said, LLThere are many similarities between AI and biotechnology, namely, the entrepreneurship and many startup firms, few products yet, but much commercial potential, a shortage of qualified talent, and a potential to create vast social change. The aspects of world forces of change are serious in that they threaten the livelihood of the U.S. economy because 70% of the U.S. output is in world markets. Abstract The consensus of government, academic, and industry leaders widely supports the strategic positioning of U.S. and Japanese research and development in mutually beneficial, two-way flows of innovation This report is derived from the IJCAI panel titled U S and Japanese Cooperation in AI and R&D Opportunities, held August 23, 1985 at the University of California at Los Angeles This panel discussed the sensitive topic of alternatives to nationalistic competitive strategies that have contributed to an extreme trade deficit surpassing $40 billion in 1985 The ideas offered by the panelists shed light on ways our countries' respective scientific communities can blend talents to achieve the best results in reducing trade frictions Each country has designated AI research as a key to unlock years of generations of technology and has directed billions of dollars to fund this development The most recognized projects are the U.S. Microelectronics Technology Computer Consortium (MCC) and Japan's Fifth Generation Computer Project (ICOT).

TED program represents the Army's first successful The Gulf War confirmed that the Abrams tank epitomizes lethality and survivability on today's battlefield. Logistically, however, the negative corollary is that the Abrams is expensive to operate, support, and maintain. Central to these costs is the maintenance of its turbine engine. Maintenance on the Abrams engine is accomplished at three levels: (1) organizational, (2) direct support, and (3) depot. Depot is usually in the United States.

Editor: AI'S IMPACT ON EMPLOYMENT Thank you for the excellent intention and effort in presenting Nils Nilsson's article on the long-term socioeconomic aspects of increasing application of artificial intelligence. Please let me offer some thoughts on the spread of technology to the third world. In the article, James Albus is quoted with agreement in saying that military conflict is inevitable if the current population explosion is not matched by a corresponding increase in affluence based on improved industrial productivity. The expansion of affluence suggested to avoid more human tragedy is certainly urgent. But it is critical that control of the sources and types of affluence are local to the areas affected.

Example from the LOOM WORDNet Knowledge Base. At the beginning, we assumed that the hyponymy relation could simply be mapped onto the subsumption relation and that the synset notion could be mapped into the notion of concept. Both subsumption and concept have the usual description logic semantics (Woods and Schmolze 1992). LOOM WORDNET knowledge base are reported in table 1. Fig-ORDNET's noun top Under Territorial_-Dominion, we find Macao and Palestine together with Trust_Territory. The Trust_Territory synset, defined as "a dependent country, administered by a country under the supervision of United Nations," denotes a general kind of country rather than a specific country such as Macao or Palestine.

ARTIFICIAL INTELLIGENCE is that part of Computer Science that concerns itself with the concepts and methods of symbolic inference and symbolic representation of knowledge. But within the last fifteen years, it has concerned itself also with signals-with the interpretation or understanding of signal data. AI researchers have discussed "signal-tosymbol transformations," and their programs have shown how appropriate use of symbolic manipulations can be of great use in making signal processing more effective and efficient. Indeed, the programs for signal understanding have been fruitful, powerful, and among the most widely recog-Many different people helped in building HASP/SIAP in many different capacities. The people acknowledged below are project leaders (*), consult.ants;

The Modified Antarctic Mapping Mission (MAMM) was conducted from September to November 2000 onboard RADARSAT. The mission plan consisted of more than 2400 synthetic aperture radar data acquisitions of Antarctica that achieved the scientific objectives and obeyed RADARSAT's resource and operational constraints. Mission planning is a time-and knowledge-intensive effort. It required over a workyear to manually develop a comparable plan for AMM-1, the precursor mission to MAMM. This article describes the design and use of the automated mission planning system for MAMM, which dramatically reduced mission-planning costs to just a few workweeks and enabled rapid generation of what-if scenarios for evaluating alternative mission designs.

A wide range of sensor-rich, networked embedded systems are being created that must operate robustly for years in the face of novel failures by managing complex autonomic processes. These systems are being composed, for example, into vast networks of space, air, ground, and underwater vehicles. Our objective is to revolutionize the way in which we control these new artifacts by creating reactive model-based programming languages that enable everyday systems to reason intelligently and enable machines to explore other worlds. A model-based program is state and fault aware; it elevates the programming task to specifying intended state evolutions of a system. The program's executive automatically coordinates system interactions to achieve these states, entertaining known and potential failures, using models of its constituents and environment.

The purpose of the AAAI-2002 Robot Rescue event is to challenge researchers to design useful robotic systems for urban search and rescue (USAR). The competition rules are written to simulate a real rescue response in a simulated disaster environment developed by the National Institute of Standards and Technology. The event comprises a competition and an exhibition. The competition is a low-fidelity simulation meant to encourage participants to contribute to the field of urban search and rescue (USAR) robotics and make them aware of the AI and engineering research challenges encountered when working within the USAR field (Casper et al. 2001). Competitors are challenged to quickly locate as many victims as possible within constraints, which provide the competitor with a sense of what a real USAR situation involves.