Agents
AAAI 2001 Spring Symposium Series Reports
Fesq, Lorraine, Atkins, Ella, Khatib, Lina, Pecheur, Charles, Cohen, Paul R., Stein, Lynn Andrea, Lent, Michael van, Laird, John, Provetti, A., Cao, S. Tran
The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2001 Spring Symposium Series on Monday through Wednesday, 26 to 28 March 2001, at Stanford University. The titles of the seven symposia were (1) Answer Set Programming: Toward Efficient and Scalable Knowledge, Representation and Reasoning, (2) Artificial Intelligence and Interactive Entertainment, (3) Game-Theoretic and Decision-Theoretic Agents, (4) Learning Grounded Representations, (5) Model-Based Validation of Intelligence, (6) Robotics and Education, and (7) Robust Autonomy.
RIACS Workshop on the Verification and Validation of Autonomous and Adaptive Systems
Pecheur, Charles, Visser, Willem, Simmons, Reid
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.
AAAI 2000 Fall Symposium Series Reports
Rose, Carolyn Penstein, Freedman, Reva, Bauer, Mathias, Rich, Charles, Horswill, Ian, Schultz, Alan, Freed, Michael, Vera, Alonso, Dautenhahn, Kerstin
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.
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
As the title indicates, Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence covers the design and development of multiagent and distributed AI systems. The purpose of this book is to provide a comprehensive overview of the field. It is an excellent collection of closely related papers that provides a wonderful introduction to multiagent systems and distributed AI.
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
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.
AAAI News
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.
Partial-Order Planning with Concurrent Interacting Actions
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.
RoboCup Rescue: A Grand Challenge for Multiagent and Intelligent Systems
Kitano, Hiroaki, Tadokoro, Satoshi
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.