Search Results for "q learning algorithm" - Page 10
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Showing 277 open source projects for "q learning algorithm"
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AHANNS
AHANNS - Amateur Homemade Artificial Neural Network Simulator
AHANNS enables the user to create and train artificial neural networks. Training is carried out by an implementation of back propagation learning algorithm. See the documentation for details. This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. ... -
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Reactor Breeder
A Genetic Algorithm for Reactors in StarMade
This software uses a genetic algorithm to "evolve" reactor designs for Schema's space-simulation game, Star-Made (http://star-made.org/). One of the more unique aspects of the game is that ship power management is not as simple as filling a cube with power generation blocks. This mechanism leads to difficulties in getting maximal power generation out of such reactors. This program rectifies this issue by using a self-organizing variant of brute force search. Much of the search space is... -
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VOC-DPM
Object detection system using deformable part models (DPMs)
...The code integrates several enhancements: a star-cascade detection algorithm to speed up screening, context rescoring (re-ranking detections using contextual information), and various optimizations like in-memory training (rather than large on-disk data files). -
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cerrla
The CERRLA algorithm, developed by Sam Sarjant
This project contains the files required to run the Cross-Entropy Relational Reinforcement Learning Agent (CERRLA) algorithm. Note that a copy of the JESS rules engine will also be required. -
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Sentence Composer
Compose the writings semi-automatically
...First, I made a chatterbot to understand the concept of "predicting" the next sentence (worked as good as the Cleverbot), then I made this program that is aided by an user to compose the new writings. SAMPLE: Input sentence was "Learning algorithm" The prefix was "transductive learning" Learning algorithm. Transduction, or transductive inference, tries to predict new outputs on specific and fixed (test) cases from observed, specific (training) cases. The simplest realization for transductive inference is the method of k-nearest neighbors. Learning to learn learns its own inductive bias based on previous experience. ...AND SO ON.... ... -
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Averaged N-Dependence Estimators - AnDE
AnDE implements A1DE and A2DE
Averaged N-Dependence Estimators (A1DE and A2DE) achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes. The resulting algorithm is computationally efficient while delivering highly accurate classification on many learning tasks. For more information, see, G. Webb, J. Boughton, Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning. 58(1):5-24 and G.I. Webb, J. Boughton, F. Zheng, K.M. Ting and H. Salem (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive {Bayesian} classification. ... -
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csg.js
Constructive solid geometry on meshes using BSP trees in JavaScript
...With CSG, you build complex 3D shapes by combining primitives using Boolean operations like union, subtract, and intersect. The library focuses on clarity and correctness: its implementation is intentionally concise and readable so developers can understand the algorithm, while still correctly handling tricky edge cases such as overlapping coplanar polygons. A WebGL-based demo shows how two solids can be combined interactively in the browser, making it a great educational tool for learning CSG concepts. The API allows you to create primitives (cubes, spheres, etc.) and then combine or transform them programmatically, producing new mesh geometry for rendering or export. ... -
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Clever Algorithms
Clever Algorithms: Nature-Inspired Programming Recipes
Clever Algorithms collects clear, cookbook-style descriptions of nature-inspired optimization and learning methods, organized so you can pick an algorithm and apply it quickly. Each entry follows a consistent template: motivation, strategy, pseudocode, parameter choices, variations, and references, making it easy to compare approaches. The catalog spans evolutionary algorithms, swarm intelligence, immune systems, simulated annealing, tabu search, and other metaheuristics, plus guidance on when and how to tune them. ... -
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Averaged N-Dependence Estimators (A1DE and A2DE) achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes. The resulting algorithm is computationally efficient while delivering highly accurate classification on many learning tasks. For more information, see, G. Webb, J. Boughton, Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning. 58(1):5-24 and G.I. Webb, J. Boughton, F. Zheng, K.M. Ting and H. Salem (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive {Bayesian} classification. ...
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ListMLE
ListMLE tool and source: A listwise algorithm for learning to rank
An implementation of ListMLE in C++. A listwise algorithm for learning to rank using likelihood loss. Author: Ngo Xuan Bach, School of Information Science, Japan Advanced Institute of Science and Technology -
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CvHMM
Discrete Hidden Markov Models based on OpenCV
This project (CvHMM) is an implementation of discrete Hidden Markov Models (HMM) based on OpenCV. It is simple to understand and simple to use. The Zip file contains one header for the implementation and one main.cpp file for a demonstration of how it works. Hope it becomes useful for your projects. -
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ListNet
ListNet tool and source: A listwise algorithm for learning to rank
An implementation of ListNet in C++. A listwise approach to learning to rank using entropy loss function. Author: Ngo Xuan Bach, School of Information Science, Japan Advanced Institute of Science and Technology -
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Stanford Machine Learning Course
machine learning course programming exercise
...Each folder corresponds to a specific algorithm or concept, making it easy for learners to navigate and practice. The exercises serve as practical, hands-on reinforcement of theoretical concepts taught in the course. This collection is valuable for students and practitioners who want to strengthen their skills in machine learning through coding exercises. -
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Machine Learning TicTacToe
TicTacToe with simple machine learning algorithm.
This is a free version of TicTacToe with little intellectual abilities. A very simple Machine Learning stuff. When I say "free", I mean "Free is like in Freedom". Even if Mr. Stallman prefers EMACS, this program was written on Vim. -
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CRF is a Java implementation of Conditional Random Fields, an algorithm for learning from labeled sequences of examples. It also includes an implementation of Maximum Entropy learning.
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CRFSharp
CRFSharp is a .NET(C#) implementation of Conditional Random Field
CRFSharp(aka CRF#) is a .NET(C#) implementation of Conditional Random Fields, an machine learning algorithm for learning from labeled sequences of examples. It is widely used in Natural Language Process (NLP) tasks, for example: word breaker, postagging, named entity recognized, query chunking and so on. CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. ... -
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PoleBalancing2D
Q-Learning Framework with example application
This is a small framework for Q(0) with a feedforward-neural net. The example application is a agent in 2D, which learns to balance a pole. -
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jsGorithm is a Javascript algorithm execution viewer that can be used as an educative tool for introductory courses on programming and algorithmics, with programs written in a subset of C/C++/Javascript. It can be used for teaching and learning.
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ProteinLasso
ProteinLasso: A Lasso regression approach to protein inference problem
ProteinLasso: In this paper, we formulate the protein inference problem as a constrained Lasso regression problem and then solve it with a fast pathwise coordinate descent algorithm. The new inference algorithm ProteinLasso explores an ensemble learning strategy to address the sparsity parameter selection problem in Lasso model. ProteinLasso is implemented in Java and can run on any Java Virtual Machine (JVM) regardless of computer architecture. -
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Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.
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BorderFlow implements a general-purpose graph clustering algorithm. It maximizes the inner to outer flow ratio from the border of each cluster to the rest of the graph.
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Optex Analyzer is a software to analyze and compare algorithms to solve approximately optimization problems. It has a GUI that allows select a set of input files containing raw algorithm results. The analysis is shown with tables and charts.
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ADWIN is an adaptive sliding window algorithm for detecting change and keeping updated statistics from a data stream, and use it as a black-box in place or counters in learning and mining algorithms initially not designed for drifting data.
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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.