Literature meetings

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(Thursday 5th June 2008 - Eliseo)
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==Purpose==
 
 
Keep everyone updated with the current state of the art literature on Swarm Intelligence. Push people to read literature and discuss it together, in order to possibly get new ideas for research in both robotics and optimization. The literature will be mainly drawn from the Swarm Intelligence journal.
 
 
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==Format==
 
 
# Presentation (10 - 30 mins)
 
# Discussion (10 - 20 mins)
 
 
Try and make your session as involving as possible for everyone. If relevant, think about possible implications of what you are presenting for the research direction of the lab as a whole - methodologies, technologies etc.
 
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==Timing & Attendance==
 
 
The weekly meetings take place, alternatively to robotics meetings, on
 
 
<center> '''Thursdays at 15.00''' </center>
 
 
Unless:
 
* A given Thursday is a public holiday, or
 
* Something very important (like a Ph.D. defense) is overlapping.
 
 
If either should happen the meeting is postponed to the next day.
 
 
'''Please indicate on this wiki page if you are not going to be able to attend a meeting''' (no later than the Friday before).
 
 
If you forget to note your absence in advance you will be severely punished and will be forced to buy a nice, big cake for the following meeting.
 
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== Thursday 12th June 2008 - Eliseo ==
 
 
'''''Paper Info'''''
 
 
* '''Title'''
 
** Ant clustering with locally weighted ant perception and diversified memory
 
 
* '''Authors'''
 
** Gilbert L. Peterson, Christopher B. Mayer, Thomas L. Kubler
 
 
* '''Summary'''
 
** The paper introduces two improvements to existing state of the art clustering algorithm based on ants. The first is the use of kernel functions as a way to increase the local perception capabilities of ants, enabling them to better distinguish between similar and dissimilar objects in their neighborhood. The second is the introduction of similarity-based memory, i.e. a very simple memory that can be equipped into single ants or in the entire ant colony and enables a better exploitation of the past experience. Results show that these improvements yield to better clustering quality and performance.
 
 
'''''Reading material'''''
 
 
* The paper is not yet published so it cannot be distributed in pdf. Paper copies can be obtained passing by Eliseo's office.
 
 
'''''People who will be absent'''''
 
 
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Revision as of 15:45, 8 January 2010

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