Welcome to the home page of the AAMAS/AOC Research Group at the Department of Computer Science, Hong Kong Baptist University.
Take a look at What's New section to find out the latest information about our group. The invited talk given by Prof. Liu at IJCAI'03 is the best place to start. There is also a What is... section where you can find a brief introduction to the research undertaken by our group. To find out more information related on our group members, research projects, group meetings, links to interesting resources, please click the links on the navigation bar above.
What's New
The following is a list of recent additions to our web. Whenever we publish a paper, organize a seminar/meeting, or add anything else to our web, we'll put a notice here. The most recent changes are listed first.
November 3, 2003
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Prof. Liu's invited talk at ISMIS'03 is added to the group home page and the resources page. |
August 29, 2003
| A link to Prof. Liu's invited talk (pdf version) at IJCAI'03 is added to the group home page and the resources page. |
| J. Liu, Web Intelligence (WI): What Makes Wisdom Web?, in Proceedings of 18th International Joint Conference on Artificial Intelligence (IJCAI-03), Acapulco, Mexico, Aug. 9-15, 2003, pages 1596-1601, Morgan Kaufmann Publishers. (Note that this paper corresponds to the above invited talk.) |
July 11, 2003
| Meetings and Members page updated |
| Many new papers added to the Projects page |
May 29, 2003
| Student Projects added |
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What Is...
AAMAS
Autonomous and Multi-Agent Systems (AAMAS) research in our group concentrates on the study of systems of autonomous intelligent entities in at least the following aspects:
Behavioral Self-Organization Architectures and Algorithms Evolutionary/Artificial Life-Based Agent Models Agentlet Dynamics Semantic Association/Mixed-Initiative Planning Virtual Environments and Synthetic Animation Multi-Agent Robotics Systems Learning and Self-Adaptation Self-Organized Vision and Motion Collective Robotics Web Intelligence (WI) and Ubiquitous Social Computing (USC) Self Organized Load Balancing Distributed Caching Time-Constrained Trading Negotiation Distributed Semantic Web Agents Information Foraging Agents Web Regularity Characterization Back to Top
AOC
Nature is full of complex systems that exhibit intelligent behavior. Having a good understanding of them will allow us to explain, predict, reconstruct and deploy them as practical solutions to hard computational problem. Common techniques for complex systems modeling can broadly be divided into top-down and bottom-up approaches. Top-down approaches start from the high-level system and treat every part of a complex system homogeneously and tend to model the average case well, where regional variation in behavior is minimal and can be ignored. However, it seems this is not always applicable. Bottom-up approaches, on the other hand, start from the smallest and simplest element of the system based on the observation that entities in a complex system are autonomous, emergent, adaptive and self-organized.
Autonomy oriented computing (AOC) is a complementary paradigm for solving hard computational problems and for characterizing the behaviors of a complex system. The first goal of AOC is to reproduce life-like behavior in computation. With detailed knowledge of the underlying mechanism, simplified life-like behavior can be used as model for a general-purpose problem solving technique. Replication of behavior is not the end, but rather the means, of these computational algorithms. The second goal of AOC is to understand the underlying mechanism of a real-world complex system by hypothesizing and repeated experimentation. The end product of these simulations is a better understanding of or explanations to the real working mechanism of the modeled system. The third goal of AOC concerns the emergence of a problem solver in the absence of human intervention. In other words, self-adaptive algorithms are desired.
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