Sriram Gopalakrishnan, Ph.D.

Sriram Gopalakrishnan, Ph.D.

AI Research Lead at J.P. Morgan Chase | Sequential-Decision Making Problems, Human-AI Interaction, & Generative AI

Embedding Directed Graphs in Potential Fields Using FastMap-D

Published in Proceedings of the 13th Annual Symposium on Combinatorial Search (SOCS 2020), 2020

Recommended citation: Gopalakrishnan, S., Cohen, L., Koenig, S., & Kumar, T. S. (2020). Embedding Directed Graphs in Potential Fields Using FastMap-D. In Proceedings of the 13th Annual Symposium on Combinatorial Search. https://ojs.aaai.org/index.php/SOCS/article/view/18520

Abstract

FastMap provides Euclidean embeddings for undirected graphs. We introduce FastMap-D, generalising embedding principles to directed, asymmetric distance metrics via continuous potential field decompositions, significantly speeding up heuristic search on directed networks.

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Recommended citation: Gopalakrishnan, S., Cohen, L., Koenig, S., & Kumar, T. S. (2020). Embedding Directed Graphs in Potential Fields Using FastMap-D. In Proceedings of the 13th Annual Symposium on Combinatorial Search.