Pack logtalk -- logtalk-3.90.1/examples/ncl/figures/NOTES.md

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This folder contains Logtalk versions of two examples of network modeling for recognizing polyhedra represented as graphs as described in the following paper:

@inproceedings{Markov1989AFF,
        title={A Framework for Network Modeling in Prolog},
        author={Z. I. Markov},
        booktitle={IJCAI},
        year={1989}
}

A copy of the paper can be downloaded from:

https://www.ijcai.org/Proceedings/89-1/Papers/013.pdf

The Logtalk version uses parametric objects to represent the concept of "net-variables" described in the paper as "global logical variables" and the coroutining library to approximate the semantics of the original examples. The object parameter variables provide object "global logical variables". The implicit use of the dif/2 constraint is mentioned in the paper third page: "(The use of a special Prolog extension, ensuring all different variables to be bound to different objects, is essential in this example. Such an extension is also available in Prolog III.)".

Note that the use of the dif library limits the backend Prolog systems that can be used to run this example to B-Prolog, ECLiPSe, XVM, SICStus Prolog, SWI-Prolog, Trealla Prolog, XSB, and YAP.

Print Logtalk, Prolog backend, and kernel versions (if running as a notebook):

%versions

Load the example:

logtalk_load(figures(loader)).

Recognize a parallelogram (the vertices rotation results in four solutions per class):

%%table
figures(_, _, _, _, _, _, _, _, _, _, _, _, _, _, _)::(
                edge(1, 2,  0, 20),
                edge(2, 3, 45, 30),
                edge(3, 4,  0, 20),
                edge(4, 1, 45, 30),
                class(Name, X, Y, Z, P)
        ).

%%table
figures(_, _, _, _, _, _, _, _, _, _, _, _, _, _, _)::(
                edge(1, 2,  0, 20),
                edge(2, 3, 45, 30),
                edge(3, 4,  0, 20),
                edge(4, 1, 45, 30),
                class(Name)
        ).

Recognize a rhombus (the vertices rotation results in four solutions per class):

%%table
figures(_, _, _, _, _, _, _, _, _, _, _, _, _, _, _)::(
                edge(a, b, 45, 10),
                edge(b, c,  0, 10),
                edge(c, d, 45, 10),
                edge(d, a,  0, 10),
                class(Name, X, Y, Z, P)
        ).

%%table
figures(_, _, _, _, _, _, _, _, _, _, _, _, _, _, _)::(
                edge(a, b, 45, 10),
                edge(b, c,  0, 10),
                edge(c, d, 45, 10),
                edge(d, a,  0, 10),
                class(Name)
        ).

Take perpendicularity into account when checking the class of a figure:

%%table
figures_split(_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _)::(
                edge(1, 2,  0, 20),
                edge(2, 3, 90, 20),
                edge(3, 4,  0, 20),
                edge(4, 1, 90, 20),
                perpendicular,
                class(Name)
        ).

%%table
figures_split(_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _)::(
                edge(a, b, 45, 10),
                edge(b, c,  0, 10),
                edge(c, d, 45, 10),
                edge(d, a,  0, 10),
                perpendicular,
                class(Name)
        ).