The structure of the book makes examples and applications, and a section such as the agent's ability to it useful for practitioners from AI and dedicated to the relationship between perceive the environment and maintain general computer science as well as multiagent systems and various knowledge about it, reason about other areas such as aviation, transportation, other research areas. This book compiles said environment, and execute particular and business. The book presents the important concepts and actions to solve tasks. The design the basics of all the components methodologies required to develop a of a single-agent system, although not required to build a multiagent system.

The Council encouraged Science and Engineering Fair, to be sometimes after an appropriate the Conference Committee to gather held May 8-10 in San Jose. Carol asked waiting period agreeable to our copublisher, extensive feedback after the 2002 conference for a volunteer to replace Mel Montemerlo The MIT Press. The Council voted to gauge how well this new as the coordinator of the judging in favor of reaffirming this policy format was received.

In order to generate plans for agents with multiple actuators, agent teams, or distributed controllers, we must be able to represent and plan using concurrent actions with interacting effects. This has historically been considered a challenging task requiring a temporal planner with the ability to reason explicitly about time. We show that with simple modifications, the STRIPS action representation language can be used to represent interacting actions. Moreover, algorithms for partial-order planning require only small modifications in order to be applied in such multiagent domains. We demonstrate this fact by developing a sound and complete partial-order planner for planning with concurrent interacting actions, POMP, that extends existing partial-order planners in a straightforward way. These results open the way to the use of partial-order planners for the centralized control of cooperative multiagent systems.

The Fourth International Conference on Autonomous Agents

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. 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.

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.

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.

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.