Search Results for "q learning algorithm" - Page 2
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Showing 39 open source projects for "q learning algorithm"
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weka outlier is an implementation of outlier detection algorithms for WEKA. CODB (Class Outliers: Distance-Based) Algorithm is the first algorithm developed using WEKA framework.
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Maui is a multi-purpose automatic topic indexing algorithm. Given a document, Maui automatically identifies its topics. Depending on the task topics are tags, keywords, keyphrases, vocabulary terms, descriptors or Wikipedia titles.
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TrimGA is a lightweight genetic algorithm library written in pure Java 6.0 that can be quickly applied to most optimization problems.
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Java package to study a clustering model described in the paper \"Novel Clustering Algorithm Based Upon Games on Evolving Network\" by Q. Li, Z. Chen, Y. He and J-P. Jiang (in arxiv: http://arxiv.org/pdf/0812.5064v1), generalizations and similar issues.
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TBLTools is a set of GATE processing resources that implements the Fast Transformation Based Learning Algorithm. You can train it to learn rules for NLP tasks such as Named Entity Recognition and Shallow parsing.
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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
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PIQLE is a Platform Implementing Q-LEarning (and other Reinforcement Learning) algorithms in JAVA. Version 2 is a major refactoring. The core data structures and algorithms are in piqle-coreVersion2. Examples are in piqle-examplesVersion2. A complete doc
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The Decision Tree Learning algorithm ID3 extended with pre-pruning for WEKA, the free open-source Java API for Machine Learning. It achieves better accuracy than WEKA's ID3, which lacks pre-pruning.Info: http://bruno-wp.blogspot.com/search/label/Softwar
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A discretization algorithm based on the Minimum Description Length. Implemented as a filter according to the standards and interfaces of WEKA, the Java API for Machine Learning. More Info: http://bruno-wp.blogspot.com/search/label/Software
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The project implements Dana Angluin's learning algorithm with intent to look into the possibility of computational learning of changing (shifting) information.
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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/.
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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.
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In imitative learning, an agent will attempt to match what is observed to their memory. By visualizing the incorrectly matches "scenes", this project will allow algorithm developers to gain a better understanding of what causes their algorithms to fail.
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Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.
