Computing the incomputable has always been a challenge. For example, in finding the busiest Turing machines (Rado) given a number of symbols and states (whimsically called busy beavers). This means either finding Turing machines that, starting from an empty input, produce more non-blank symbols in their output tapes before halting than any other Turing machine [...]

I was awarded a 3rd Place Prize in this year’s FQXi contest Is Reality Digital or Analog? by the Foundational Questions Institute for my work entitled The World is Either Algorithmic or Mostly Random. The winners were announced at this year’s World Science Festival in New York City. Based on the combined ratings of the [...] <http://feeds.feedburner.com/~ff/AnimaExMachina?a=aaTeyxGfHHU:prN5fYNxsGY:yIl2AUoC8zA><http://feeds.feedburner.com/~ff/AnimaExMachina?a=aaTeyxGfHHU:prN5fYNxsGY:dnMXMwOfBR0><

We present a method for estimating the complexity of an image based on the concept of Bennett's logical depth. We use this measure to classify images by their information content. The method provides a means for evaluating and classifying objects by way of their visual representations. <http://feeds.feedburner.com/~ff/AnimaExMachina?a=IW9tuhKc3ew:FZL33B1SA0s:yIl2AUoC8zA><http://feeds.feedburner.com/~ff/AnimaExMachina?a=IW9tuhKc3ew:FZL33B1SA0s:dnMXMwOfBR0><http://feeds.feedburner.com/~ff/AnimaExM

======================================== The Shortest Universal Turing Machine Implementation Contest ANNOUNCEMENT 23 Dec – 2008 http://www.mathrix.org/experimentalAIT/TuringMachine.html ======================================== Contest Overview ============ In the spirit of the busy beaver competition though related to program-size complexity, we are pleased to announce the “Shortest Universal [...] <http://feeds.feedburner.com/~ff/AnimaExMachina?a=gv22a5CUWXQ:xCxFzzQEhHk:yIl2AUoC8zA><http://fee

A method for studying the qualitative dynamical properties of abstract computing machines based on the approximation of their program-size complexity using a general lossless compression algorithm is presented. It is shown that the compression-based approach classifies cellular automata (CA) into clusters according to their heuristic behavior, with these clusters showing a correspondence with Wolfram's main classes of CA behavior. A Gray code-based numbering scheme for initial conditions and a c