Showing posts from December, 2010

Why facebook stopped working for me

Facebook offers great functionalities, it is easy, fun, extensible... However, it seems that like many things which are positive for many people (e.g. automobiles), they get overused with unintended consequences (e.g. traffic jams). OK, so I have 400+ friends on facebook. The problem is that I could spare like 5 minutes every other day to check the news feed. With so many people in my feed, I get what was posted 2 hours ago at most. Sure, there are ways of blocking applications, creating filters (e.g. with Better FB ), but this does not work for me. There are just too many posts I am not interested about, but I am interested in few things that most people post about. It is difficult to categorize. Where is artificial intelligence when it is needed? I believe that algorithms similar to anti-spam filters would be immensely useful on social networks. For example, I am interested about the English postings of my Iranian friends, but I cannot make much of their Farsi posts... For users, i

Deadline Extended, Final CfP: Special Issue on Complex Networks, Artificial Life

Call for Papers Special Issue on Complex Networks Artificial Life Journal Motivation As a result of the quality of the Complex Networks track at the ALife XII conference last August in Odense, Denmark and the interest of the attendants; we announce a call for papers for a special issue on this theme for the Artificial Life Journal. Many complex systems are amenable to be described as networks. These include genetic regulatory, structural or functional cortical networks, ecological systems, metabolism of biological species, author collaborations, interaction of autonomous systems in the Internet, etc. A recent trend suggests to study common  global  topological features of such networks, e.g. network diameter, clustering coefficients, assortativity, modularity, community structure, etc. Various network  growth models  have also been proposed and studied to emulate the features of the real-world networks, e.g. the preferential attachment model, which explains scale-free power law degre

Paper Published: The sigma profile: A formal tool to study organization and its evolution at multiple scales, Complexity

Gershenson, C. (2010). The sigma profile: A formal tool to study organization and its evolution at multiple scales. Complexity,  first published online: 10 NOV 2010. DOI: 10.1002/cplx.20350 Abstract The σ profile is presented as a tool to analyze the organization of systems at different scales, and how this organization changes in time. Describing structures at different scales as goal-oriented agents, one can define σ ∈ [0,1] (satisfaction) as the degree to which the goals of each agent at each scale have been met. σ reflects the organization degree at that scale. The σ profile of a system shows the satisfaction at different scales, with the possibility to study their dependencies and evolution. It can also be used to extend game theoretic models. The description of a general tendency on the evolution of complexity and cooperation naturally follows from the σ profile. Experiments on a virtual ecosystem are used as illustration. Full text (se

Science catching up science fiction

The science: mice are born with genetic material of two males (fresh news). The science fiction: dreams of a teenager (~12 years ago).  [in Spanish...]