AAAI Publications, Thirteenth Annual Symposium on Combinatorial Search

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Embedding Directed Graphs in Potential Fields Using FastMap-D
Sriram Gopalakrishnan, Liron Cohen, Sven Koenig, T. K. Satish Kumar

Last modified: 2020-05-08

Abstract


Embedding undirected graphs in a Euclidean space has many computational benefits. FastMap is an efficient embedding algorithm that facilitates a geometric interpretation of problems posed on undirected graphs. However, Euclidean distances are inherently symmetric and, thus, Euclidean embeddings cannot be used for directed graphs. In this paper, we present FastMap-D, an efficient generalization of FastMap to directed graphs. FastMap-D embeds vertices using a potential field to capture the asymmetry between the to-and-fro pairwise distances in directed graphs. FastMap-D learns a potential function to define the potential field using a machine learning module. In experiments on various kinds of directed graphs, we demonstrate the advantage of FastMap-D over other approaches.


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