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  2. Logo (programming language) - Wikipedia

    en.wikipedia.org/wiki/Logo_(programming_language)

    A general-purpose language, Logo is widely known for its use of turtle graphics, in which commands for movement and drawing produced line or vector graphics, either on screen or with a small robot termed a turtle. The language was conceived to teach concepts of programming related to Lisp and only later to enable what Papert called "body ...

  3. LibreLogo - Wikipedia

    en.wikipedia.org/wiki/LibreLogo

    LibreLogo is an integrated development environment (IDE) for computer programming in the programming language Python, which works like the language Logo using interactive vector turtle graphics. Its final output is a vector graphics rendition within the LibreOffice suite. It can be used for education and desktop publishing.

  4. Gekko (optimization software) - Wikipedia

    en.wikipedia.org/wiki/Gekko_(optimization_software)

    GEKKO is an extension of the APMonitor Optimization Suite but has integrated the modeling and solution visualization directly within Python. A mathematical model is expressed in terms of variables and equations such as the Hock & Schittkowski Benchmark Problem #71 [2] used to test the performance of nonlinear programming solvers.

  5. Turtle graphics - Wikipedia

    en.wikipedia.org/wiki/Turtle_graphics

    Turtle graphics are often associated with the Logo programming language. [2] Seymour Papert added support for turtle graphics to Logo in the late 1960s to support his version of the turtle robot, a simple robot controlled from the user's workstation that is designed to carry out the drawing functions assigned to it using a small retractable pen set into or attached to the robot's body.

  6. Quadratic programming - Wikipedia

    en.wikipedia.org/wiki/Quadratic_programming

    The NAG Library has routines for both local and global optimization, and for continuous or integer problems. Python: High-level programming language with bindings for most available solvers. Quadratic programming is available via the solve_qp function or by calling a specific solver directly. R (Fortran)

  7. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    Written in C++ and published under an MIT license, HiGHS provides programming interfaces to C, Python, Julia, Rust, R, JavaScript, Fortran, and C#. It has no external dependencies. A convenient thin wrapper to Python is available via the highspy PyPI package. Although generally single-threaded, some solver components can utilize multi-core ...

  8. Divide-and-conquer algorithm - Wikipedia

    en.wikipedia.org/wiki/Divide-and-conquer_algorithm

    Divide and conquer is a powerful tool for solving conceptually difficult problems: all it requires is a way of breaking the problem into sub-problems, of solving the trivial cases, and of combining sub-problems to the original problem.

  9. General Problem Solver - Wikipedia

    en.wikipedia.org/wiki/General_Problem_Solver

    General Problem Solver (GPS) is a computer program created in 1957 by Herbert A. Simon, J. C. Shaw, and Allen Newell (RAND Corporation) intended to work as a universal problem solver machine. In contrast to the former Logic Theorist project, the GPS works with means–ends analysis .