In this report, I present a summary of the activities that took place during the Fourth International Conference on Autonomous Agents, which took place in Barcelona Spain from 3 to 7 June 2000.

The AAAI-2000 Workshop Program was held Sunday and Monday, 3031 July 2000 at the Hyatt Regency Austin and the Austin Convention Center in Austin, Texas. The 15 workshops held were (1) Agent-Oriented Information Systems, (2) Artificial Intelligence and Music, (3) Artificial Intelligence and Web Search, (4) Constraints and AI Planning, (5) Integration of AI and OR: Techniques for Combinatorial Optimization, (6) Intelligent Lessons Learned Systems, (7) Knowledge-Based Electronic Markets, (8) Learning from Imbalanced Data Sets, (9) Learning Statistical Models from Rela-tional Data, (10) Leveraging Probability and Uncertainty in Computation, (11) Mobile Robotic Competition and Exhibition, (12) New Research Problems for Machine Learning, (13) Parallel and Distributed Search for Reasoning, (14) Representational Issues for Real-World Planning Systems, and (15) Spatial and Temporal Granularity.

This article describes the winning entries in the 2000 Association for the Advancement of Artificial Intelligence Mobile Robot Competition. The robots, developed by Swarthmore College, all used a modular hybrid architecture designed to enable reflexive responses to perceptual input. Within this architecture, the robots integrated visual sensing, speech synthesis and recognition, the display of an animated face, navigation, and interrobot communication. In the Hors d'Oeuvres, Anyone? event, a team of robots entertained the crowd while they interactively served cookies; and in the Urban Search-and-Rescue event, a single robot autonomously explored a section of the test area, identified interesting features, built an annotated map, and exited the test area within the allotted time.

Disaster rescue is one of the most serious social issues that involves very large numbers of heterogeneous agents in the hostile environment. The intention of the RoboCup Rescue project is to promote research and development in this socially significant domain at various levels, involving multiagent teamwork coordination, physical agents for search and rescue, information infrastructures, personal digital assistants, a standard simulator and decision-support systems, evaluation benchmarks for rescue strategies, and robotic systems that are all integrated into a comprehensive system in the future. For this effort, which was built on the success of the RoboCup Soccer project, we will provide forums of technical discussions and competitive evaluations for researchers and practitioners. Although the rescue domain is intuitively appealing as a large-scale multiagent and intelligent system domain, analysis has not yet revealed its domain characteristics. The first research evaluation meeting will be held at RoboCup-2001, in conjunction with the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI-2001), as part of the RoboCup Rescue Simulation League and RoboCup/AAAI Rescue Robot Competition. In this article, we present a detailed analysis of the task domain and elucidate characteristics necessary for multiagent and intelligent systems for this domain. Then, we present an overview of the RoboCup Rescue project.

The Innovative Applications of Artificial Intelligence Conference was held 18-22 July 1999 in Orlando, Florida. Ramasamy Uthurusamy was the Program Chair and Barbara Hayes-Roth was the Program Co-Chair. Although all the IAAI-99 papers and talks were certainly interesting and important, we present in this special issue of AI Magazine only a select subset because of page and other limitations. We include two invited talks and four applications as a snapshot of IAAI-99.

Based Search," by Peter Clark, John Thompson, Heather Holmback, and Lizbeth Duncan of the Boeing Co., demonstrated a concept-based search engine using an AI thesaurus with unambiguous control terms and relationships for ontology links for finding relevance when searching for human experts in the field.

I was asked to give a visionary talk about the future applications of Artificial Intelligence technology; but I should warn you that I'm actually not very good as a visionary. Most of my predictions about what will happen in the industry don't come true even though they ought to. So I'm not going to tell you what the future holds; what I will do is to point out some of the technological trends that are at work. The outline of the talk is as follows: I'll start off by looking at the previous IAAI conferences and reflect on what we've learned from them. Then I'll look at what's changing in the hardware base that sets the context for all the computer applications we do. I think that will lead to interesting new viewpoints. Next I'll sketch what applications might arise from this new viewpoint. Finally, I'll discuss how the development of practical applications ought to interact with the scientific enterprise of trying to understand intelligence, in particular, human intelligence.

First, if a team's collaboration is better than the other team, some of the statistical Score books are useful for analyzing teammate. FALL 2000 25 national conference on artificial intelligence innovative applications of artificial intelligence spring symposium series fall symposium series aaai press ai mgazine member's electronic library aaai fellows classic paper award distinguished service award allen newell award mobile robot competition robot exhibition botball tournament discounts on ai books aaai intel science and engineering awards effective expository writing award ai topics website discounts on journals scientific policy grants for workshops, conferences, and symposia technical reports electronic directory of ai scientists

The CMUNITED-99 simulator team became the 1999 RoboCup simulator league champion by winning all 8 of its games, outscoring opponents by a combined score of 110-0. CMUNITED-99 builds on the successful CMUNITED-98 implementation but also improves on it in many ways. This article gives an overview of CMUNITED-99's improvements over CMUNITED-98.

With the growing importance of multiagent team-work, tools that can help humans analyze, evaluate, and understand team behaviors are also becoming increasingly important. To this end, we are creating isaac, a team analyst agent for post hoc, offline agent-team analysis. ISAAC'S novelty stems from a key design constraint that arises in team analysis: Multiple types of models of team behavior are necessary to analyze different granularities of team events, including agent actions, interactions, and global performance. These heterogeneous team models are automatically acquired by machine learning over teams' external behavior traces, where the specific learning techniques are tailored to the particular model learned. Additionally, ISAAC uses multiple presentation techniques that can aid human understanding of the analyses. This article presents ISAAC'S general conceptual framework and its application in the RoboCup soccer domain, where ISAAC was awarded the RoboCup Scientific Challenge Award.