44 projects tagged "Artificial Intelligence"
EO is a template-based, ANSI-C++ evolutionary computation library that helps you to write your own stochastic optimization algorithms quickly. Evolutionary algorithms form a family of algorithms inspired by the theory of evolution, and solve various problems. They evolve a set of solutions to a given problem in order to produce the best results. These are stochastic algorithms because they iteratively use random processes. The vast majority of these methods are used to solve optimization problems, and may be also called "metaheuristics". They are also ranked among computational intelligence methods, a domain close to artificial intelligence. With the help of EO, you can easily design evolutionary algorithms that will find solutions to virtually all kind of hard optimization problems, from continuous to combinatorial ones.
MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms. It addresses the two most common scenarios in collaborative filtering: rating prediction (e.g. on a scale of 1 to 5 stars), and item prediction from implicit feedback (e.g. from clicks or purchase actions). It contains dozens of recommender engines, including state-of-the-art matrix factorization methods. It also supports real-time updates to the recommender engines, storing engines to disk and reloading them again, and several evaluation measures to compare the accuracy of different recommender system methods. Three command-line programs that offer most of the functionality contained in the library are included.
Beneath A Binary Sky is an engine that simulates a world in which robots controlled by programs can live, work, fight, and even bear new children. The long-term goal of the project is to create a fully configurable engine that can simulates any kind of world, from simple to complex ones with many rules and events.
pyECTOR is a chatterbot which learns from what people say. It is based on an artificial intelligence architecture that is inspired by Copycat, an AI system from Mitchell and Hofstadter. The Concept Network it uses is a mix between neural and semantic networks. It uses co-occurrences to compute the influence of one semantic node on another. The links are statistically weighted.
Algraeph is a tool for manual alignment of linguistic graphs, such as phrase structure trees or dependency structures, where each node corresponds to a subsequence of the analyzed input sentence. It allows you to express the similarity between two graphs by aligning their nodes and attaching relation labels to these alignments. Graphs are read from one or more graphbanks (or treebanks) in the GraphML or Alpino formats. Alignment relations are user-defined and are stored in a simple XML format, which can be used for further processing. The resulting parallel graph corpus is a useful data set for many tasks in computational linguistics and natural language processing.
Python Web Graph Generator is a threaded Web graph (Power law random graph) generator. It can generate a synthetic Web graph of about one million nodes in a few minutes on a desktop machine. It supports both directed and undirected graphs. It implements a threaded variant of the RMAT algorithm. A little tweak can produce graphs representing social networks or community networks. It can also output connected components in a graph.