Untitled. Thanks for your interest in Copycat! Copycat is written in Common Lisp. The system is unfortunately rather outdated: it will not run as is without some updates for modern versions of Common Lisp, and some platform-specific modifications to the graphics files. I am hoping that it will be rewritten in a more platform independent way sometime soon. I am still making the source files available. To get the source files, go to : and at your home machine, untar the file to get the source files. If your system can't deal with tar files, then go to and individually get each source file. To get Jim Marshall's Metacat project, go to: Scott Bolland of the University of Queensland wrote a Java version of Copycat and a tutorial; the web site is.
Melanie Mitchell. Complexity Explorer. Pattern Recognition on the Web. Pattern recognition. Pattern recognition algorithms generally aim to provide a reasonable answer for all possible inputs and to perform "most likely" matching of the inputs, taking into account their statistical variation. This is opposed to pattern matching algorithms, which look for exact matches in the input with pre-existing patterns. A common example of a pattern-matching algorithm is regular expression matching, which looks for patterns of a given sort in textual data and is included in the search capabilities of many text editors and word processors.
In contrast to pattern recognition, pattern matching is generally not considered a type of machine learning, although pattern-matching algorithms (especially with fairly general, carefully tailored patterns) can sometimes succeed in providing similar-quality output to the sort provided by pattern-recognition algorithms. Overview[edit] Probabilistic classifiers[edit] They output a confidence value associated with their choice. . To output labels . . . Where. Butterfly - The Secret Life of Chaos - BBC 4 Preview Introduction to Complex Systems. By David Kirshbaum I. Introduction: Complex Systems Theory : Basic Definition II. Four Important Characteristics of Complexity: III. I. A Complex System is any system which involves a number of elements, arranged in structure(s) which can exist on many scales. Previously, when studying a subject, researchers tended to use a reductionist approach which attempted to summarize the dynamics, processes, and change that occurred in terms of lowest common denominators and the simplest, yet most widely provable and applicable elegant explanations.
But since the advent of powerful computers which can handle huge amounts of data, researchers can now study the complexity of factors involved in a subject and see what insights that complexity yields without simplification or reduction. Scientists are finding that complexity itself is often characterized by a number of important characteristics: (II.1) Self-Organization(II.2) Non-Linearity(II.3) Order/Chaos Dynamic(II.4) Emergent Properties. Examples. Complexity and Emergence.