As a result, they knowledge of an agent (that is, its epistemic coarse-grained level of abstraction, KBwould argue, it is not possible to discuss state) can be characterized as the Ss can be characterized in terms of two the knowledge of a system independently collection of all possible worlds that components: (1) a knowledge base, encoding of the task context in which are consistent with the knowledge the knowledge embodied by the system is meant to operate. I won't held by the agent. If the knowledge of the system, and (2) a reasoning engine, go into too many details here because the agent is complete, then the epistemic which is able to query the knowledge a detailed discussion of the declarative state contains only one world. A base, infer or acquire knowledge from versus the procedural argument is well nice feature of Levesque and Lakemeyer's external sources, and add new knowledge beyond the scope of this review. The treatment of epistemic logic is that to the knowledge base. Levesque important point to make is that in contrast to many other treatments and Lakemeyer's The Logic of Knowledge Levesque and Lakemeyer's approach is of modalities, the discussion is reasonably Bases deals with the "internal logic" of situated in a precise AI research easy to follow for people who are a KBS: It provides a formal account of paradigm, which considers knowledge not experts in the field. This is the result the interaction between a reasoning bases as declaratively specified, task-independent of two main features of this analysis: engine and a knowledge base.

This article is an edited transcript of a lecture given at IJCAI-99, Stockholm, Sweden, on 4 August 1999. The article summarizes concepts, principles, and tools that were found useful in applications involving causal modeling. The principles are based on structural-model semantics in which functional (or counterfactual) relationships representing autonomous physical processes are the fundamental building blocks. The article presents the conceptual basis of this semantics, illustrates its application in simple problems, and discusses its ramifications to computational and cognitive problems concerning causation.

The debut of the AI in the News column elsewhere in this issue of AI Magazine created a good opportunity to introduce the professional community to the AI Topics web site, home of the AI in the news virtual page. Although AI Topics is designed for the lay public, it serves a much larger audience.

This article presents an overview and survey of current work in case-based reasoning (CBR) integrations. There has been a recent upsurge in the integration of CBR with other reasoning modalities and computing paradigms, especially rule-based reasoning (RBR) and constraint-satisfaction problem (CSP) solving. CBR integrations with modelbased reasoning (MBR), genetic algorithms, and information retrieval are also discussed. This article characterizes the types of multimodal reasoning integrations where CBR can play a role, identifies the types of roles that CBR components can fulfill, and provides examples of integrated CBR systems. Past progress, current trends, and issues for future research are discussed.

RoboCup-2001 was the Fifth International RoboCup Competition and Conference. It was held for the first time in the United States, following RoboCup-2000 in Melbourne, Australia; RoboCup-99 in Stockholm; RoboCup-98 in Paris; and RoboCup-97 in Osaka. This article discusses in detail each one of the events at RoboCup-2001, focusing on the competition leagues.

Botball is a national program in which teams of middle and high school students design, build, and program small autonomous mobile robots to compete in a highly charged interactive (but nondestructive) tournament. Botball students learn to program in c, construct feedback and control loops, create electromechanical systems, and integrate it all together while they work on a team. Botball takes place in regional tournaments across the country and culminates in a National Botball Tournament traditionally hosted by the Association for the Advancement of Artificial Intelligence at its annual conference. This program puts reusable equipment into schools and, at the Botball Teacher Workshops, trains teachers in robotics and the integration of robotics into their curriculum. Botball appeals to a wide variety of students and brings out the best in each, challenging them to solve realworld problems in a dynamic environment at their own level.

The RoboCup Rescue Physical Agent League Competition was held in the summer of 2001 in conjunction with the AAAI Mobile Robot Competition Urban Search and Rescue event, eerily preceding the September 11 World Trade Center (WTC) disaster. Four teams responded to the WTC disaster through the auspices of the Center for Robot-Assisted Search and Rescue (CRASAR), directed by John Blitch. The four teams were Foster- Miller and iRobot (both robot manufacturers from the Boston area), the United States Navy's Space Warfare Center (SPAWAR) group from San Diego, and the University of South Florida (USF). Blitch, through his position as program manager for the Defense Advanced Research Projects Agency (DARPA) Tactical Mobile Robots Program, was a supporter of the competition; he also served as a member of the rules committee and a judge. USF participated by chairing the rules committee, judging, assisting with the logistics, providing commentary, and demonstrating tethered and wireless robots whenever entrants had to skip around during the competition. Based on our experiences and history, we were asked to comment on the validity of the competition. The CRASAR collective experience suggests that most of the basic rules of the competition matched reality because the rules accurately reflected deployment scenarios, but the National Institute of Standards and Technology (NIST) Standard Test Course, and hardware or software approaches forwarded by competitors in last summer's event, missed the mark. This article briefly reviews the types of robots and missions used by CRASAR at the WTC site, then discusses the robotassisted search and rescue effort in terms of lessons for the competition.

"Neats and scruffies alike were mesmerized by the animal-like responses of the robots demonstrated there," says Bonasso. "At the end of "This won't be a slick, polished competition. Over the AAAI Mobile Robot Competition and Exhibition years, the event and AI Magazine have served as was born. The event has endured to a venue for this and several other intellectual become the oldest AIcentric robotics competition debates, including sensing versus modeling, in the world. As we near the end of our color-based versus shape-based object recognition, first decade, it seems worthwhile to reflect on and reactive control versus symbolic what the origins of the event were, how it has planning for robot navigation (Balch et al. evolved, and where it is headed. The contest immediately took on two important but apparently conflicting roles: First, it provided a target for research in AI and robotics; in Pete Bonasso's words, the event was cast "in the spirit of trying to develop as animate, responsive, and intelligent robot behavior as possible" (Dean and Bonasso 1993).

The search and rescue efforts involving structural joint rules committee from RoboCup and collapse and other urban environments (Fire AAAI brought two communities together to 1993). The main task of USAR is to recover live develop the rules and scoring method. Robots involved with USAR must were four registered teams in the competition: identify victims and send back the locations to (1) Sharif University, (2) Swarthmore College, trained medical rescue personnel for removal (3) Utah State University, and (4) the University of the victims from the collapsed area. Additionally, several teams Robot Rescue League rules, designed by the exhibited their robots in the rescue arena, rules committee, keep the USAR task in focus including the University of South Florida and by addressing several issues that arise in real the University of Minnesota. This article discusses USAR situations, such as the time to transport the 2001 Robot Rescue event: the and set up the robot; the number of personnel course, the rules, the research approaches of required to run the robot; and, most importantly, the participants, and the final scores.

A short summary of each robot demonstrates the variety in form and function among the exhibitions. Programming a robot is often a complex and Intelligence (AAAI) Mobile Robot involved task. By allowing the robot to learn and wide variety in behavior and form, the robots practice behaviors at run time, Darrin Bentivegna in the exhibition created a sense of the broad aims to create robots that can learn range of function in the robotic community. The exhibition has involving air hockey against a humanoid provided past AI researchers with new perspectives robot. After a human has specified some primitives and ideas.