DCAI '10 Call for papers

The International Symposium on Distributed Computing and Artificial Intelligence (DCAI 2010) is an annual forum that will bring together ideas, projects, lessons, etc.. associated with distributed computing, artificial intelligence and its applications in different themes. The workshop will be organized into CEDI 2010 that will be held at the Polytechnic University of Valencia in September 7-10th, 2010.

This symposium will be organized by the Biomedicine, Intelligent System and Educational Technology Reseach Group (BISITE) of the University of Salamanca. The technology transfer in this field is still a challenge and for that reason this type of contributions will be specially considered in this symposium. This conference is the forum in which to present application of innovative techniques to complex problems.

The artificial intelligence is changing our society. Its application in distributed environments, such as the Internet, electronic commerce, mobile communications, wireless devices, distributed computing, and so on is increasing and is becoming an element of high added value and economic potential, both industrial and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both academic and business areas is essential to facilitate the development of systems that meet the demands of today's society.

DCAI 2010 is sponsored by the IEEE Systems Man and Cybernetics Society, Spain Section Chapter. The accepted papers included in DCAI 2010 proceedings (long papers, short papers and doctoral consortium papers) will be published by Springer Verlag in the Advances in Intelligent and Soft-Computing series of Springer. At least one of the authors will be required to register and attend the symposium to present the paper in order to include the paper in the conference proceedings.

(Read the complete Call for Papers)

[WI-IAT09] Intelligent Social Network Modelling

by Ronald Yager

Fuzzy sets to represent linguistic concepts, reducing the human.machine gap. A common vocablary is needed, so human can use linguistic terms and machines can use fuzzy representation to represent the same concepts and understand each other. For example: about Age {young, old, senior, 23, about 40}

Granular computing is a technique that can be used to link linguistic (human) and mathmatic (machine) concepts. It extensd the capabilities for analyzing social relational networks by enabling tue use of human like concepts with fuzzy sets and granulat technologies. A Social network is actually a set object.... a lot of maths and concepts about the structure of the graphs in social networks now... I prefer to listen instead of to write, sorry.

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[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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