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artificial-intelligence (18)



Charlemagne
Charlemagne is a genetic programming application that includes both a commandline client and an interactive console mode. It is written in Python and Lisp, and is user extensible to some degree in both languages. It features built-in input-output mapping support and provides the ability to define complex fitness calculations in Lisp or Python.

Dbacl
'dbacl' is a digramic Bayesian text classifier. Given some text, it calculates the posterior probabilities that the input resembles one of any number of previously learned document collections. It can be used to sort incoming email into arbitrary categories such as spam, work, and play, or simply to distinguish an English text from a French text. It fully supports international character sets, and uses sophisticated statistical models based on the Maximum Entropy Principle.

Deduce
'Deduce' is an artificial intelligence program which accepts natural language sentences as input. These sentences describe properties and relationships between objects, (for example, "Spot is a dog", "A liquid will evaporate", or "Water does not flow uphill"). The user can then ask questions against that input, to which Deduce will attempt to answer using deductive reasoning techniques.

Discrete Event Calculus Reasoner
The Discrete Event Calculus Reasoner allows a programmer to add common-sense reasoning capabilities to programs. It supports deduction/temporal projection, abduction/planning, postdiction, and model finding. It allows default reasoning about action, change, space, and mental states. It is based on the event calculus, a comprehensive and highly usable logic-based formalism. It helps applications understand the world, make inferences, adapt to unexpected situations, and be more flexible.

FANN
Fast Artificial Neural Network Library (fann) implements multi-layer feedforward networks that support both fully connected and sparsely connected networks. It supports execution in fixed point arithmetic to allow for fast execution on systems with no floating point processor. To overcome the problems of integer overflow, the library calculates a position of the decimal point after training and guarantees that integer overflow cannot occur with this decimal point. FANN is designed to be fast, versatile, and easy to use. Several benchmarks have been executed to test its performance. It is significantly faster than other libraries on systems without a floating point processor, and comparable to other highly optimized libraries on systems with a floating point processor.

GNOWSYS Heckert gnu.small.png
GNOWSYS is an acronym for "Gnowledge Networking and Organizing SYStem." It is a web based object oriented database server with each object provided by an unique URL. GNOWSYS is a tool to construct and store persistently a Gnowledge Base (GB). The GB consists of the following three groups of constructor classes (system and temporal classes under development):

PredicateGroup: relationType, relation, functionType, function

Object Group: metaType, class, object (with provision to have classes and objects of declarative, procedural, encapsulated, temporal etc.)

Structure Group: systemType, system, flowType, flow, processType, process

GNOWSYS indexes data and metadata of objects in a catalogue for faster queries. Optionally, data can remain anywhere on the Internet (only the metadata stays in the database). Surrogates of procedures (classes, functions, and system calls) can also be installed in the database as special objects. These procedures execute as web services, so users can design applications without writing program in any programming language by specifying the semantics of a program and mapping the elements of the program to the surrogates of procedures is sufficient for GNOWSYS to test the application design.

Ikaros
'Ikaros' is a framework for writing and running component-based simulators. It is currently used for simulations of brain areas and learning models, but is general enough to be easily used for any discrete-time simulation. A simulation consists of modules connected in the simulator, with connections specified in an XML file. There are socket-based hooks for adding a GUI. The package contains a number of modules and complete documentation for working with the framework.

Infovore
Infovore is designed to merge large data sets such as Freebase and DBpedia, producing 100% valid RDF output at high speed because it uses the Hadoop Framework

KNIME
KNIME [naim] is a user-friendly graphical workbench for the entire analysis process: data access, data transformation, initial investigation, powerful predictive analytics, visualisation and reporting. The open integration platform provides over 1000 modules (nodes), including those of the KNIME community and its extensive partner network.

MLPACK
MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. MLPACK contains the following algorithms: Collaborative Filtering, Density Estimation Trees, Euclidean Minimum Spanning Trees, Fast Exact Max-Kernel Search (FastMKS), Gaussian Mixture Models (GMMs), Hidden Markov Models (HMMs), Kernel Principal Component Analysis (KPCA), K-Means Clustering, Least-Angle Regression (LARS/LASSO), Local Coordinate Coding, Locality-Sensitive Hashing (LSH), Logistic regression, Naive Bayes Classifier, Neighbourhood Components Analysis (NCA), Non-negative Matrix Factorization (NMF), Principal Components Analysis (PCA), Independent component analysis (ICA), Rank-Approximate Nearest Neighbor (RANN), Simple Least-Squares Linear Regression (and Ridge Regression), Sparse Coding, Tree-based Neighbor Search (all-k-nearest-neighbors, all-k-furthest-neighbors), Tree-based Range Search.

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