The guideline for the survey paper is now available. (htm)
Please choose your topic early as the due date is in mid-February (Feb 15, 24:00 ).
Students are request to sent in the following information to discuss your topic.
I will give you hints based on your profile.
Please tell me the following about you in your email:
. Undergraduate / other degree (MBA / MSc, etc.) program:
. Undergraduate / current / other degree projects:
. Current MSc program and course taken:
. Current / Previous Job (job function and business sector):
. email address (prefer "permant" one that can contact you after graduation)
. mobile phone (optional)
2009年1月20日 星期二
Lecture 3 and 5
We shall continue to use negotiation as an example to illustrate how ontologies and semantics help in MAS. Besides helping the agent to understand concepts, ontologies and semantics also help humans to understand their requirements and therefore help the specification of requirements and preferences better.
For example, in Yahoo auction, can you easily find a digital camera with the requirement of "better than 3 megapixals" and "fitting CF or SD card"? With ontologies, we can.
After the motivating example, we shall then go over some technical details of RDF and OWL, with nowadays are essential for many other "intelligent" or searching applications, not just for agents.
For example, in Yahoo auction, can you easily find a digital camera with the requirement of "better than 3 megapixals" and "fitting CF or SD card"? With ontologies, we can.
After the motivating example, we shall then go over some technical details of RDF and OWL, with nowadays are essential for many other "intelligent" or searching applications, not just for agents.
2009年1月12日 星期一
Lecture 2
One of you commented the concepts of agents are still fuzzy for them.
So, in Lecture 2, we introduced some internal mechanisms and architecture for agents, especially the Belief-Desire-Intension agent architecture.
We showed a detail example of a concrete BDI agent the paper on negotiation based on constraints as to illustrate the functioning of agents:
D.K.W. Chiu, S.C. Cheung, P.C.K. Hung, and H.F. Leung. Constraint-based Negotiation in a Multi-Agent Information System with Multiple Platform Support, 37th Hawaii International Conference on System Sciences (HICSS37), Jan 2004. (ppt)(doc)
We shall go over the rest of the paper in the next lecture.
So far, we have introduced both the macroscopic (top down) and microscopic (bottom up) view of agents and MAS.
So, in Lecture 2, we introduced some internal mechanisms and architecture for agents, especially the Belief-Desire-Intension agent architecture.
We showed a detail example of a concrete BDI agent the paper on negotiation based on constraints as to illustrate the functioning of agents:
D.K.W. Chiu, S.C. Cheung, P.C.K. Hung, and H.F. Leung. Constraint-based Negotiation in a Multi-Agent Information System with Multiple Platform Support, 37th Hawaii International Conference on System Sciences (HICSS37), Jan 2004. (ppt)(doc)
We shall go over the rest of the paper in the next lecture.
So far, we have introduced both the macroscopic (top down) and microscopic (bottom up) view of agents and MAS.
Lecture 1
We have introduced what are agents and what are Multi-agent Systems (MAS).
We have also introduced a motivating case study that uses agents as software building blocks
for a service-oriented (telecom) enterprise. This serves also as the vision what the ultimate product that we aim at in the (near) future, because now we have the enabling technologies ready, together with the arising need of business intelligence from various businesses. If we were to use classical examples of agents in robotics and industrial control, those are probably too far away from your experience and work. We shall refer back to this case from time to time for discussion.
One of you asked the difference between Web Services and agents. Similiar to Web services, agents not just serve as software building blocks but also as integration mechanism, having interfaces and protocols. However, agents means more:
We have also introduced a motivating case study that uses agents as software building blocks
for a service-oriented (telecom) enterprise. This serves also as the vision what the ultimate product that we aim at in the (near) future, because now we have the enabling technologies ready, together with the arising need of business intelligence from various businesses. If we were to use classical examples of agents in robotics and industrial control, those are probably too far away from your experience and work. We shall refer back to this case from time to time for discussion.
One of you asked the difference between Web Services and agents. Similiar to Web services, agents not just serve as software building blocks but also as integration mechanism, having interfaces and protocols. However, agents means more:
- Web services are usually just reactive (on invocation), but not proactive
- Web services are normally for individual invocations like functions and procedures, but agents normally run continuously as a long-life process to help its owner / delegator (e.g., appointment agents), i.e., autonomous
- Agents can include intelligence and flexible actions (especially exception handling), which is not common in current Web services. (flexibility)
As mentioned in this paper, this is a foundation for future detailed design, analysis, and research. So, if you are interested in any part of this (say, capability matching, location-based allocation), you are encourages to choose one of this as your survey (horizontal / in-depth approach) as well as your course topic.
Alternatively, you may also choose another domain of your choice, usually integrating knowledge from your job (vertical approach), your degree project, or your favorite courses.
We emphasize on practical relevance. So, please make sure that you are able to give examples to illustrate your work.
2009年1月8日 星期四
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