Search Results for "q learning algorithm" - Page 4

Foad is an open source software which receive an EKG Signal from scanner, WFDB database or heart sensors. Finding patient disease started by taking Fourier transform (FFT) from input signal and extract a single cycle. Based on some heuristic algorithm the most important feature like P , Q , R , S , T captured and feed to trained neural network. and so the final decision made by CNN library. As mentioned before this software also capable do some image processing on scanned paper to lower the final costs.

Very basic cellular automaton implementation in C#. Based upon the "Togetherness" algorithm described at http://www.hermetic.ch/pca/tg.htm.

This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in С++.

ANT is a lightweight implementation in C of a kind of artificial neural net called Multilayer Perceptron, which uses the backpropagation algorithm as learning method. The package includes an introductory example to start using artificial neural nets.

The Free Connectionist Q-learning Java Framework is an library for developing learning systems. Keywords: qlearning, artificial intelligence, alife, neural nets, neural networks, machine learning, reinforcement learning unsupervised learning agents lejos

Classic game solved with MinMax algorithm (full solution tree) and simple Heuristics. Specially for learning and teaching computer AI

KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.

A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.

MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning. The code is well documented and easy to extend, especially for adding new weak learners.

RL++ is an easy to use modular open source library for Reinforcement Learning written in C++. It includes learning algorithms (TD, Sarsa, Q) as well as the implementation of value function representations (LookupTable, TileCoding, Neuronal Network).

Algorithm that can generate any given series of probabilities G, using only fair coins. The algorithm creates a Huffman tree by decomposing any probability P into a sum of probabilites Q, where each Q is a power of 1/2. Than using the coins, the tra

A genetic algorithm framework to allow the evolution of synapse weights and topologies of artificial neural networks.

Weka++ is a collection of machine learning and data mining algorithm implementations ported from Weka (http://www.cs.waikato.ac.nz/ml/weka/) from Java to C++, with enhancements for usability as embedded components.