Search Algorithms
Showing 23 of 23 projects
A collection of popular algorithms and data structures implemented in Swift with detailed explanations.
A high-performance string library leveraging SIMD and SWAR to accelerate search, hashing, sorting, and edit distances across C, C++, Python, Rust, and more.
A JAX-native library implementing Monte Carlo tree search algorithms like AlphaZero and MuZero for reinforcement learning research.
A collection of well-known computer science algorithms and data structures implemented in Objective-C for educational purposes.
A C++ library for fast approximate nearest neighbor searches in high-dimensional spaces with automatic algorithm selection.
A Swift framework providing implementations of common data structures and algorithms with educational examples.
A fast, extensible, multi-platform C# library for implementing genetic algorithms in .NET applications.
A learned index structure enabling fast lookups, range searches, and updates on billions of items with minimal space usage.
A comprehensive Swift library for creating and manipulating weighted, unweighted, directed, and undirected graphs with built-in algorithms.
A Go implementation of a trie data structure with algorithms for extremely fast prefix and fuzzy string searching.
A lightweight Ruby playground with clean implementations of core AI algorithms for learning and experimentation.
A lightweight Ruby playground with clean, readable implementations of core AI algorithms for learning and experimentation.
A vector space search engine, vector database, and key/value store for efficient string processing and vector operations.
Common Lisp implementation of classic AI algorithms from the 'Artificial Intelligence: A Modern Approach' textbook.
A high-performance, memory-efficient Go implementation of Adaptive Radix Trees with zero-allocation searches and ordered iteration.
A Rust library providing fast linear time and space suffix arrays with full Unicode support.
A flexible Rust framework for building and running genetic algorithm simulations for optimization and search problems.
A fast, parallel, and extensible genetic algorithms framework implemented in Rust for solving optimization problems.
A collection of classic algorithms and data structures implemented in Erlang for educational and practical use.
A comprehensive collection of data structures and algorithms implemented in the Crystal programming language.
A Pacman AI project implementing search algorithms like DFS, BFS, UCS, and A* for navigation and food collection.
A modular framework for executing genetic algorithms in Rust with a simple API.
A Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms.
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