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About — PRAC 1.0.1 documentation

We are happy to announce Version 1.0 of PRAC! As the tasks of autonomous manipulation robots get more complex, the tasking of the robots using natural-language instructions becomes more important. Executing such instructions in the way they are intended often requires robots to infer missing, and disambiguate given information using lots of common and commonsense knowledge. During my research work, I proposed the concept of. In your own scripts, see API-Specification. Daniel Nyga ( nyga @. Daniel Nyga an...

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About — PRAC 1.0.1 documentation | actioncores.org Reviews

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We are happy to announce Version 1.0 of PRAC! As the tasks of autonomous manipulation robots get more complex, the tasking of the robots using natural-language instructions becomes more important. Executing such instructions in the way they are intended often requires robots to infer missing, and disambiguate given information using lots of common and commonsense knowledge. During my research work, I proposed the concept of. In your own scripts, see API-Specification. Daniel Nyga ( nyga @. Daniel Nyga an...

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3 try out online

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5 feature overview

6 getting started

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About — PRAC 1.0.1 documentation | actioncores.org Reviews

https://actioncores.org

We are happy to announce Version 1.0 of PRAC! As the tasks of autonomous manipulation robots get more complex, the tasking of the robots using natural-language instructions becomes more important. Executing such instructions in the way they are intended often requires robots to infer missing, and disambiguate given information using lots of common and commonsense knowledge. During my research work, I proposed the concept of. In your own scripts, see API-Specification. Daniel Nyga ( nyga @. Daniel Nyga an...

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actioncores.org

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Python Module Index — PRAC 1.0.0 documentation

http://www.actioncores.org/py-modindex.html

Tools for Probabilistic Natural-language Instruction Interpretation.

2

Getting Started — PRAC 1.0.0 documentation

http://www.actioncores.org/setup.html

Tools for Probabilistic Natural-language Instruction Interpretation. Laquo; Feature Overview. Tools for Pro. ». This software suite works out-of-the-box on Linux and Windows 64-bit machines. The source code is publicly available under BSD License:. Python 2.7 (or newer) with Tkinter installed. On Windows, Tkinter is usually shipped with Python. On Linux, the following packages should be installed (tested for Ubuntu):. You will also need the following python packages:. You can install them via.

3

Tools for Probabilistic Natural-language Instruction Interpretation — PRAC 1.0.0 documentation

http://www.actioncores.org/tools.html

Tools for Probabilistic Natural-language Instruction Interpretation. Tools for Probabilistic Natural-language Instruction Interpretation. Graphical Tools and Editors. Laquo; Getting Started. PRAC Query-Tool ». Tools for Probabilistic Natural-language Instruction Interpretation. After the installation, all of these tools will be located in the. Directory (which, if you’ve set up your environment correctly, is within your system. A graphical inference tool. Graphical Tools and Editors. The tool works with.

4

API-Specification — PRAC 1.0.0 documentation

http://www.actioncores.org/apidoc.html

Tools for Probabilistic Natural-language Instruction Interpretation. Laquo; PRAC Query-Tool. Comes with an easy-to-use API, which lets you use the modules provided by. Of which each solves an own inference task conveniently in your own applications. A PRACModule is represented by an instance of the class. Each module provides a. File containing the predicate declarations for the MLN of the respective module and a. The PRAC reasoning system is represented by an instance of the class. And a list of natural...

5

Feature Overview — PRAC 1.0.0 documentation

http://www.actioncores.org/features.html

Tools for Probabilistic Natural-language Instruction Interpretation. Getting Started ». Interpretation of natural-language instructions. Identification of action roles. Extraction of object properties. Refinement of action cores and action roles.

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open-ease.org

» Natural-language understanding for intelligent robots

http://www.open-ease.org/nlp-overview

Open Knowledge for AI-Enabled Robots. Natural-language understanding for intelligent robots. Knowledge about actions and objects is represented as Probabilistic Robot Action Cores (PRAC), which can be thought of as generic event patterns that enable a robot to infer important information that is missing in an original natural-language instruction. PRAC models are represented in Markov Logic Networks, a powerful knowlegde represenation formalism combing first-order logic and probability theory.

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About — PRAC 1.0.1 documentation

We are happy to announce Version 1.0 of PRAC! As the tasks of autonomous manipulation robots get more complex, the tasking of the robots using natural-language instructions becomes more important. Executing such instructions in the way they are intended often requires robots to infer missing, and disambiguate given information using lots of common and commonsense knowledge. During my research work, I proposed the concept of. In your own scripts, see API-Specification. Daniel Nyga ( nyga @. Daniel Nyga an...

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