AbductiveLearning
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ABLkit
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ABLkit/examples/zoo
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README.md

Zoo Example

This example shows a simple implementation of Zoo. In this task, attributes of animals (such as presence of hair, eggs, etc.) and their targets (the animal class they belong to) are given, along with a knowledge base which contain information about the relations between attributes and targets, e.g., Implies(milk == 1, mammal == 1). The goal of this task is to develop a learning model that can predict the targets of animals based on their attributes.

Run

pip install -r requirements.txt
python main.py

Usage

usage: main.py [-h] [--loops LOOPS] 

Zoo example

optional arguments:
  -h, --help            show this help message and exit
  --loops LOOPS         number of loop iterations (default : 3)
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An efficient Python toolkit for Abductive Learning (ABL), a novel paradigm that integrates machine learning and logical reasoning in a unified framework.

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