{"id":20718500,"url":"https://github.com/knowm/ahah","last_synced_at":"2025-04-23T14:12:16.323Z","repository":{"id":11397353,"uuid":"13842614","full_name":"knowm/AHaH","owner":"knowm","description":"AHaH Machine Learning","archived":false,"fork":false,"pushed_at":"2024-04-30T20:34:21.000Z","size":1006,"stargazers_count":26,"open_issues_count":0,"forks_count":11,"subscribers_count":7,"default_branch":"master","last_synced_at":"2025-04-23T14:12:07.628Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Java","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/knowm.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2013-10-24T19:52:46.000Z","updated_at":"2025-03-03T04:17:10.000Z","dependencies_parsed_at":"2022-08-31T05:40:21.102Z","dependency_job_id":null,"html_url":"https://github.com/knowm/AHaH","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/knowm%2FAHaH","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/knowm%2FAHaH/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/knowm%2FAHaH/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/knowm%2FAHaH/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/knowm","download_url":"https://codeload.github.com/knowm/AHaH/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250447991,"owners_count":21432164,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-17T03:13:51.684Z","updated_at":"2025-04-23T14:12:16.276Z","avatar_url":"https://github.com/knowm.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"## AHaH!\n\nA machine learning framework based on Anti-Hebbian and Hebbian (AHaH) neural plasticity. This project is an archive of code referenced from our 2014 paper: [AHaH Computing–From Metastable Switches to Attractors to Machine Learning](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0085175).\n\n## Description \n\nThe AHaH! project is a set of tools that can be used to solve a wide range of artificial intelligence \nand machine learning problems. All key functionality is based on operations that can be attained \nthrough use of an Anti-Hebbian and Hebbian (AHaH) Node. An AHaH Node is a perceptron neuron operating \nthe AHaH plasticity rule. The AHaH Node has been mapped to physical memristor circuitry \nand NPU development is ongoing. By restricting machine learning algorithms to functions that can \nbe attained with the AHaH Node, the AHaH! software provides a bridge between the CPU of today and \nthe NPUs of tomorrow.\n\nThe AHaH Node is universal. Its attractor states are universal logic gates and optimal classification \nboundaries. It can operate in supervised, semi-supervised or unsupervised modes and has shown \nsolutions to classification, unsupervised feature extraction and clustering, motor control, and \ncombinatorial optimization. Capabilities such as tracking of non-stationary statistic and unsupervised \nhealing have also been demonstrated. The AHaH node is a \"building block\" from which a universe of \nmachine learning capabilities are now emerging. Currently the AHaH! project has specific modules targeting \nthe following areas of machine learning:\n\n1. Metastable Switch Memristor Model\n1. Functional and Circuit-based AHaH Node Models\n1. Supervised and Unsupervised Classification\n1. Unsupervised Feature Extraction and Clustering\n1. Unsupervised Robotic Actuation\n1. Combinatorial Optimization\n1. Signal Prediction and Forecasting\n\n## License\n\nAll software is copyright (c) 2013 M. Alexander Nugent Consulting and licensed under the \nM. Alexander Nugent Consulting Research License Agreement.\n\nSee LICENSE.txt for more details.\n\nSome source files for working with the MNIST data in the module 'ahah-samples' (MnistManager.java, MnistDbFile.java, MnistImageFile.java, and MnistLabelFile.java) are copyright alex pankov and we've included the source code in compliance with the 'Artistic License'. (https://code.google.com/p/mnist-tools/ß)\n\n## Building\n\nAHaH! is built with Maven.\n\n    cd path/to/ahah-parent\n    \n#### Install to local repo\n\n    mvn clean install\n    \n#### maven-license-plugin\n\n    mvn license:check\n    mvn license:format\n    mvn license:remove\n    \n#### JavaDocs\n\n    mvn javadoc:aggregate \n\n## Running the Software\n\nAll the sample applications that are part of the AHaH! project can be run from the command line, and a Java JRE \nversion 6 or higher is needed. For each sample app, a description, tips for running the app, and the argument list\nis given in the corresponding source code. Each app is configured to take a list of parameters which you can use to \ntweak and experiment with. The default argument values are in parentheses. \n\n## Questions or Help\n\nPlease email M. Alexander Nugent Consulting at i@alexnugent.name for any questions or licensing inquiries.\n\n## More Info\nProject Site: \u003chttp://knowm.org/open-source/ahah/\u003e  \nExample Code: \u003chttp://knowm.org/open-source/ahah/ahah-example-code\u003e  \nChange Log: \u003chttp://knowm.org/open-source/ahah/ahah-change-log\u003e  \nJava Docs: \u003chttp://knowm.org/javadocs/ahah/index.html\u003e  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fknowm%2Fahah","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fknowm%2Fahah","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fknowm%2Fahah/lists"}