DANN

From Syncleus Wiki

**dANN Information**
Description	An Artificial Intelligence Library written in Java.
Last Activity	Today
License	OSCL Type C
IRC Room	#dANN on irc.freenode.org
Homepage	dANN
Distributions	Binary ZIP w/JavaDoc Binary Tarball w/JavaDoc Source ZIP Soutce Tarball
Documentation	Javadoc repository Javadoc for SVN trunk Javadoc for stable release
Development	svn://svn.syncleus.com/dANN TRAC Bug & Ticket Tracking Hudson Continuous Integration

dANN is an Artificial Intelligence and Artificial Genetics library targeted at employing conventional techniques as well as acting as a platform for research & development of novel techniques. As new techniques are developed and proven to be effective they will be integrated into the core library. It is currently written in Java, C++, and C#. However only the java version is currently in active development. If you want to obtain a version other than the java version you will need to get it directly from SVN.

Our intentions are two fold. First, to provide a powerful interface for programs to include conventional artificial neural network technology into their code. Second, To act as a testing ground for research and development of new AI concepts. We provide new AI technology we have developed, and the latest algorithms already on the market. In the spirit of modular programming the library also provides access to the primitive components giving you greater control over implementing your own unique AI algorithms. You can either let our library do all the work, or you can override any step along the way.

dANN currently implements several conventional as well as new algorithms inspired by its biological counterparts. The following is an incomplete list of some of the libraries features:

Graph Theory
- Search
  - Path Finding
    - A*
    - Dijkstra
    - Bellman-Ford
    - Johnson
    - Floyd-Warshall
  - Optimization
    - Hill Climbing Local Search
- Graph Drawing
  - Hyperassociative Map
    - 3D Hyperassociative Map Visualization
Evolutionary Computing
- Genetic Algorithms
- Genetic Wavelets
Naive Classifier
- Naive Bayes Classifier
- Naive Fisher Classifier
Data Processing
- Signal Processing
  - Cooley Tukey Fast Fourier Transform
- Language Processing
  - Word Parsing
  - Word Stemming
    - Porter Stemming Algorithm
Graphical Models
- Bayesian Networks
  - Dynamic Bayesian Networks
    - Hidden Markov Models
      - Baum–Welch Algorithm
      - Layered Hidden Markov Models
      - Hierarchical Hidden Markov Models
Artificial Neural Networks
- Activation Function Collection
- Backprop Networks
  - Feedforward Networks
- Self Organizing Maps
- 3D Network Visualization
Mathematics
- Statistics
  - Markov Chains
    - Markov Chain Monte Carlo (Parameter Estimation)
- Complex Numbers
- N-Dimensional Vectors
  - 3D Vector Visualization
- Linear Algebra
  - Cholesky Decomposition
  - Hessenberg Decomposition
  - Eigenvalue Decomposition
  - LU Decomposition
  - QR Decomposition
  - Singular Value Decomposition

We've included a package of examples. Some examples included are:

3-input XOR
8 layer Hyperassociative Map
Neural Image Compression
3D Color Maping to 2D/1D Space
Travelling Salesman Problem (TSP)
Wavelet Genetics
Microphone Spectrum Analyzer (FFT)
Path Finding Editable Grid

dANN is provided under the OSCL Type-C license.

Some documents you should take a look at if your new to dANN:
Using the Library
Using the Examples

The SVN is the best place for obtaining the latest source. However if you use the SVN for obtaining and using the source please consider providing feedback so we can take your suggestions into consideration.

If you need any help installing, compiling, or patching this software in any way at all please feel free to contact us. We cant promise support, but we do encourage you to try. We will do our best to offer our help.