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OpenNARS
OpenNARS is the open source version of the NARS project, licensed under GNU GPL v2.
This project attempts to uniformly explain and reproduce many cognitive facilities, including reasoning, learning, planning, etc, so as to provide a unified theory, model, and system for AI as a whole. The ultimate goal of this research is to build a thinking machine.
What makes NARS different from conventional computer systems is its ability to learn from its experience and to work with insufficient knowledge and resources.
If you are interested in learning more, the [Overview Tour](Tour Overview) provides a high level view of the system and its implementation. Further resources are linked to in the tour, and are also listed below. For more information on the theory of NAL, take a look at the References page for links to relevant texts.
The current stable versions of the system are available for download. Each version contains a JAR file and some working examples. Java 8 is needed to run the recent versions. There is a discussion group of this project.
Pages
| General | |
| ProjectStatus | The current status and the plan for the near future of the project. |
| FAQ | Theory & Software FAQ |
| Tours | |
| [Overview](Tour Overview) | A high-level overview of this NARS implementation. |
| [Plugin System](Tour PluginSystem) | A high-level overview of the plugin system. |
| Component Descriptions | |
| [InferenceControl](Component Inference-Control) | The control aspect of NARS. |
| [Plugins](Component Plugins) | How plugins can help, what they need to fulfill to be valid, and what plugins we have. |
| [InputOutputFormat](Component Input-Output-Format) | The input/output format of the system |
| [DataStructures](Component Data-Structures) | What the different data structures represent |
| [StampInNARS](Component Stamp-In-NARS) | The design and function of Stamp in NARS. |
| NARS Theory | |
| [PerceptionInNARS](Discussion Perception-In-NARS) | How to do perception in NARS |
| [ReinforcementLearning](Discussion Reinforcement-Learning) | NARS in the RL domain. |
| [ProceduralLearning](Discussion Procedural-Learning) | Learning temporal and procedural knowledge |
| [NaturalLanguageProcessing](Discussion Natural-Language-Processing) | How to provide natural language experience. |
| Examples and Guides | |
| [Videos](Tutorial Videos) | Description of the Video Examples |
| [ApplicationPrograms](Tutorial Application-Programs) | Example Programs using OpenNARS as AI. |
| [Multi-StepExamples](Tutorial Multi-Step-Examples) | Inference Examples |
| [SingleStepTestingCases](Tutorial Single-Step-Testing-Cases) | Expected results of inference rules |
| VariableUsage | When to use what variable |
| [GraphicalUserInterface](Tutorial Graphical-User-Interface) | How to work with and what it displays. |
| [DataAndKnowledgeBases](Tutorial Data-And-Knowledge-Bases) | How to connect NARS to databases and knowledge bases. |
| Version Descriptions | |
| [OpenNarsOneDotSix](Version OpenNARS-One-Dot-Six) | Functions and remaining issues of Open-Nars 1.6.x. |
| [OpenNARSOneDotSixDotOne](Version OpenNARS-One-Dot-Six-Dot-One) | Everything about OpenNARS-1.6.1. |
| [OpenNARSOneDotSixDotTwo](Version OpenNARS-One-Dot-Six-Dot-Two) | What is new in OpenNARS-1.6.2. |
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