Search Results for "hard"

...In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot of power and complexity. Write less code and iterate faster leaving the hard stuff to us. Rubix ML utilizes a versatile modular architecture that is defined by a few key abstractions and their types and interfaces. Train models in a fraction of the time by installing the optional Tensor extension powered by C. Learners such as neural networks will automatically get a performance boost.

PetoronHash2 (PH2) is a standalone ARX-based sponge construction that combines: A 4096-bit internal permutation core A sponge/duplex architecture with explicit capacity separation An extendable-output function (XOF) Memory-hard (HARD) and burn (BURN) modes A structured tagged absorb scheme A parameterized architecture suitable for hashing, KDF, and stress-oriented derivation PH2 is designed as a wide-state cryptographic primitive with explicit domain separation and configurable output length. https://github.com/01alekseev/PetoronHash2 Petoron | Ivan Alekseev | MIT license

Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.

MicroGP (µGP, ugp) is a versatile optimizer able to outperform both human experts and conventional heuristics in finding the optimal solution of hard problems. It is an evolutionary algorithm since it mimics some principles of the Neo-Darwinian paradigm. ⚠️ A new version is available on https://github.com/squillero/microgp4

...For example, for working with internal application resource paths referencing a "sandboxed" virtual filesystem (like with PhysicsFS). Platform-specific path support is mainly intended for tools (e.g. map editor) which need to share a common code base (and perhaps some hard-coded resources) with the main sandboxed application (e.g. game).

A Constraint-Based Local Search solver for the Water Retention on Magic Squares-problem. The problem is a very hard combinatorial optimisation problem, invented by Craig Knecht. More can be read about it at: http://en.wikipedia.org/wiki/Water_retention_on_mathematical_surfaces Craig's website for the problem: http://www.knechtmagicsquare.paulscomputing.com/ The solver is mainly based on the theory and ideas from my bachelor thesis, which I wrote at Uppsala University, Sweden, for the Astra Group which does research about Constraint Programming and related technologies: Water Retention on Magic Squares with Constraint-Based Local Search http://urn.kb.se/resolve?...

A paint program where the canvas is the visual cortex of a simple kind of artificial intelligence. You paint with the mouse into its dreams and it responds by changing what you painted gradually. There will also be an API for using it with other programs as a general high-dimensional space. Each pixel's brightness is its own dimension. Bayesian nodes have exactly 3 childs because that is all thats needed to do NAND in a fuzzy way as Bayes' Rule which is NAND at certain extremes. NAND can be...

Don't hard-code data-structures for Artificial Intelligence (AI). Evolve them (and control flow) as cycles of arrays in arrays with size constraints based on other array sizes (at specific index) in terms of range, multiply, exponent, or permutation. No working code yet. Whats there now is an extension of GigaLineCompile which would become part of Human AI Net, but there are other projects to finish before I can come back to this one.

Easy To Use Collection Classes For C And C++ The Memory Structures Library (MemSL) has implementations of structures (i.e. AVL trees, threaded trees, dynamic hashing, ...) that are extremely hard to find and far harder to implement.

Mr. Logister is a resource scheduling application that uses genetic algorithms to find the best utilization and allocation of resources. The scheduler understands hard constraints like free/busy time and soft constraints like suitability and preferences.