It studies information, which typically manifests itself mathematically via various flavours of entropy. Another side of information theory is algorithmic information theory, which centers around notions of complexity.
For a long time researchers from all disciplines have avoided the use of universal mathematical measures of information theory (beyond the traditional computable, but limited, Shannon information entropy), measures such as Kolmogorov-Chaitin complexity, Solomonoff-Levin universal induction or Bennett's logical depth, as well as other related measures, citing the fact that they are uncomputable.
These measures are, however, upper or lower semi-computable and are therefore approachable from below or above. For example, lossless compression algorithms can approximate Kolmogorov-Chaitin complexity (a compressed string is a sufficient test of non-randomness) and applications have proven to be successful in many areas. Nevertheless, compression algorithms fail to compress short strings and do not represent an option for approximating their Kolmogorov complexity. This online calculator provides a means for approximating the complexity of binary short strings for which no other method has existed until now by taking advantage of the formal connections among these measures and putting together several concepts and results from theoretical computer science.
Researchers at Carlos III University of Madrid and the University of Zaragoza theoretically predict, in a scientific study, that contact networks have no influence on cooperation among individuals. These researchers have mathematically examined what occurs when groups of people who behave as the experiments say have to decide whether or not to cooperate, and how the existence of cooperation, globally or in the group, depends on the structure of the interactions.
So, I've written an article of that title for the wonderful American Scientist magazine—or rather, Part I of such an article. This part explains the basics of Kolmogorov complexity and algorithmic information theory: how, under ...
Sharing your scoops to your social media accounts is a must to distribute your curated content. Not only will it drive traffic and leads through your content, but it will help show your expertise with your followers.
How to integrate my topics' content to my website?
Integrating your curated content to your website or blog will allow you to increase your website visitors’ engagement, boost SEO and acquire new visitors. By redirecting your social media traffic to your website, Scoop.it will also help you generate more qualified traffic and leads from your curation work.
Distributing your curated content through a newsletter is a great way to nurture and engage your email subscribers will developing your traffic and visibility.
Creating engaging newsletters with your curated content is really easy.