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  2. Rule 30 - Wikipedia

    en.wikipedia.org/wiki/Rule_30

    Rule 30 is an elementary cellular automaton introduced by Stephen Wolfram in 1983. [2] Using Wolfram's classification scheme, Rule 30 is a Class III rule, displaying aperiodic, chaotic behaviour. This rule is of particular interest because it produces complex, seemingly random patterns from simple, well-defined rules.

  3. Rule 184 - Wikipedia

    en.wikipedia.org/wiki/Rule_184

    In his book A New Kind of Science, Stephen Wolfram points out that rule 184, when run on patterns with density 50%, can be interpreted as parsing the context-free language describing strings formed from nested parentheses. This interpretation is closely related to the ballistic annihilation view of rule 184: in Wolfram's interpretation, an open ...

  4. Elementary cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Elementary_cellular_automaton

    A second way to investigate the behavior of these automata is to examine its history starting with a random state. This behavior can be better understood in terms of Wolfram classes. Wolfram gives the following examples as typical rules of each class. [4] Class 1: Cellular automata which rapidly converge to a uniform state.

  5. Rule 110 - Wikipedia

    en.wikipedia.org/wiki/Rule_110

    In 2004, Matthew Cook published a proof that Rule 110 with a particular repeating background pattern is Turing complete, i.e., capable of universal computation, which Stephen Wolfram had conjectured in 1985. [2] Cook presented his proof at the Santa Fe Institute conference CA98 before publication of Wolfram's book A New Kind of Science.

  6. File:Wolfram alpha solution.pdf - Wikipedia

    en.wikipedia.org/.../File:Wolfram_alpha_solution.pdf

    This file contains additional information, probably added from the digital camera or scanner used to create or digitize it. If the file has been modified from its original state, some details may not fully reflect the modified file.

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  8. Matching wildcards - Wikipedia

    en.wikipedia.org/wiki/Matching_wildcards

    In computer science, an algorithm for matching wildcards (also known as globbing) is useful in comparing text strings that may contain wildcard syntax. [1] Common uses of these algorithms include command-line interfaces, e.g. the Bourne shell [2] or Microsoft Windows command-line [3] or text editor or file manager, as well as the interfaces for some search engines [4] and databases. [5]

  9. New Jersey fines firms $40K for sports betting violations

    www.aol.com/jersey-fines-firms-40k-sports...

    New Jersey gambling regulators have handed out $40,000 in fines to two sportsbooks and a tech company for violations that included taking bets on unauthorized events, and on games that had already ...