https://github.com/guicho271828/dsama

Implementation of Double-Stage Action Model Acquisition
https://github.com/guicho271828/dsama

Last synced: 29 days ago
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Implementation of Double-Stage Action Model Acquisition

• Host: GitHub
• URL: https://github.com/guicho271828/dsama
• Owner: guicho271828
• License: other
• Created: 2020-02-03T18:47:26.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2020-03-13T15:24:17.000Z (almost 5 years ago)
• Last Synced: 2024-10-15T14:11:00.791Z (3 months ago)
• Language: Common Lisp
• Size: 1.86 MB
• Stars: 2
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

        

# Dsama - Implementation of Double-Stage Action Model Acquisition

Implementation for DSAMA system in [1]

[1] Asai, M. 2019. "Neural-Symbolic Descriptive Action Model from Images: The Search for STRIPS" https://arxiv.org/abs/1912.05492

## Usage

TBP

## Dependencies

This library is at least tested on implementation listed below:

+ SBCL 1.4.12 on X86-64 Linux 4.4.0-145-generic (author's environment)

Also, it depends on the following libraries:

+ cl-sat :

    

+ arrow-macros by *hipeta* :

    arrow-macros provides clojure-like arrow macros and diamond wands.

+ dataloader :

    

+ trainable-object :

    

+ remlic :

    

+ cl-random-forest :

    

+ serializable-object :

    

+ numcl :

    

+ function-cache by *Acceleration.net * :

    A Simple Caching Layer for functions

+ cl-json by ** :

    JSON in Lisp. JSON (JavaScript Object Notation) is a lightweight data-interchange format.

+ iterate by ** :

    Jonathan Amsterdam's iterator/gatherer/accumulator facility

+ alexandria by *Nikodemus Siivola , and others.* :

    Alexandria is a collection of portable public domain utilities.

+ trivia by *Masataro Asai* :

    NON-optimized pattern matcher compatible with OPTIMA, with extensible optimizer interface and clean codebase

## Installation

## Author

* Masataro Asai ([email protected])

## Copyright

Copyright (c) 2019 Masataro Asai ([email protected])

# License

Licensed under the LLGPL License.