[WI-IAT09] Self-organization and agent-based simulation

A session with short papers, so I have to be ready.
 
Methodologies for self-organising systems: a SPEM approach
Mariachiara Puviani, Giovanna Di Marzo Serugendo, Regina Frei and Giacomo Cabri
 
Late :-( I,m sorry But it seems interesting. Take a look at the paper
 
Self-organization of peers in agent societies
Martin Purvis
 
Goal: to investigate gossip-based mechanism for self-organization of agents divided into groups: Decentralized, scalable and with partial information. The problem domain used is sharing digital goods in electronic societies. Can it work in a decentralized way (without supervisor)?
 
Sharing incurs a cost: the donor have a cost and the receiver receives the benefit. How agents can be «forced» to cooperate and share goods? First 100 iterations, agents play and gossip. After 100 iterations, they can move to other group.
 
Showing results about how groups are finally separated and well-defined. Why are agents leaving a group? (i) tolerance level is met (others do not share enough) or (ii) benefits are not improving.
 
 
An Autonomy-Oriented Paradigm for Self-Organized Computing
Jiming Liu
 
Typical application areas of AOC: hard problems and complex systems. Related work: discrete-time propagation models or immunization strategies for restraining virus spreading (hey, guy, it’s a short paper… when are you going to begin?) OK. decentralized search for immunization problem. The entity tries o find the node with the highest degree in its local environment. If these nodes are protected, the virus spreading can be delayed or even stopped. Possitive feedback is used to rapidly discover a good set of high-connected nodes at early stages.
 
 
Simulation of the Rungis Wholesale Market: lessons on the calibration, validation and usage of a Cognitive Agent-based Simulation
Philippe Caillou, Corentin Curchod, and Tiago Baptista
 
Justa paper about how a concrete problem has been solved (simulated) using agents. Not interesting for me. Sorry.
 
 
Silicon Coppélia: Integrating three affect-related models for establishing richer agent interaction
Matthijs Pontier and Ghazanfar Siddiqui

Goal: a robot that could interact with humans (I guess, Because I hardly can hear him… a microphone! good). Emotional models formed by the integration of 3 models: CoMERG, I-PEFiC and EMA. It uses a emotion regulation model (Gross). These approaches models important aspects of human affective behavior, but all of them miss out something important.

Proposal and simulation experiments. Something that wonders me is how utility values are calculated and emotions can be perfectly described just by a number. That’s because I don’t believe in utility-base models (I can model this as «utili-base models likelihood = -1» :-) Anyway, examples seems very complex and with a sufficient number of variables/parameters.

So they can model things as irrational decision or emotions based on believes quite well. Interesting.
 
 
Transition Process Distinction in Multiagent Organization
Eric Matson

A low-level paper… (hardware related, I mean :-) How organizations can be embedded on physical devices? Over the time, the organization evolves from its initial state untilo it reaches some state of global satisfaction.

All is based on the concept of transition rather than reorganization. Computationally, they ae very different problems. I must read this paper. It sounds interesting and promising. Furthermore, can be useful for our Android agents.
 

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[WI-IAT09] Social networks: reputation and monetization models

CCR : A Model for Sharing Reputation Knowledge Across Virtual Communities
Nurit Gal-Oz

Working with private identities of separate virtual communities (Tric -Deustche Telecom-) and reputation mechanisms to share information among different communities. The process is formed by 3 blocks
1.- Enabling preconditions

  • first
  • category matching level: [0,1] value representing community correlation based
  • third
  • domain confidence

Interesting: one of the measures ids is based on Shannon entropy of the domains (I need o revise that again)

2.- Conversion of reputation values
3.- Attribute matching (some kind of ontology alignment) as a [0,1] value, with some confidence level (certainty)
Showing an example of travel agencies :-), looking for a hotel in Milano, using communities in Trip Advisor, Expedia and Booking.

Monetizing User Activity on Social Networks – Challenges and Experiences
Meenakshi Nagarajan, Kamal Baid, Amit Sheth, and Shaojun Wang

Well-known monetization models for the Web, but not easy on Web 2.0 and SNS. Actually, advertisement-based models are used with marginal success, due to (i) informal nature of content, non-policed content and because people are there to network. So, at least, the ads have to consider: (i) identify monetizable posts (intents behind users posts) and (ii) identifying keywords on user’s comments.

Consider that people write sentences, not keywords or phrases, so the system has to be ready to analyze that to locate action patterns around entities. The example: how people seek for information. Patterns used are «where do I find…. does anyone know how… someone tell me where…» So all these patters matches with a seeking pattern in the Candidate Pool and the system can identify the question (this is very similiar to dialog characterization for agents -see AIWS slides-)

Monetization potential is calculated from this seeking score and calculating a transactional intention score for each one of them.  All test has been done off-line!! What about the cost? Because it’s important to do that on-line.

A Composite calculation for author activity in Wikis: accuracy needed
Janette Lehmann

Interesting title, but I barely can hear her :-(… oh!, better with the microphone.

Analysis of social interaction spaces (wikis, blogs, twitter…) evaluation activity, dynamics, identifying communities and topics, so they can improve existing infrastructures. They use SONIVIS as visualization tools. And today she is going to speak about wikis. Motivation: to evaluate author activity. They activity is characterized by (i) the number of changes/versions, (ii) a betweenness centrality measure among authors, (iii) significant content: frequency an author has added a term to a page and the importance of this term. This measure is normalized. These values are combined in the final author contribution. This measure is dynamic, so a cumulative author contribution can be calculated.

The example uses the English Wikipedia articles about virtual reality. A six-month period has been analyzed. Results are in the paper.

Model for Voter Scoring and Best Answer Selection in Community Q&A Services
Chung Tong Lee

The problem: how to select the best answer in Q&A communities (as Yahoo!Answers). A Voting Score mechanism is presented, based on a fixed point basis.

Voting is affected by (i) social bias -vote based on answerer, not in the quality of the answer, (ii) personal gain. The formula for the voting and the fixed point characterization is presented (see the paper). Some examples to model the voting (simulations) using random voting and ballot stuffing simulation. Zipf’s law used for generate random votes  (entropy measure). Results again in the paper.

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