Dynamic potential search on weighted graphs

Daniel Gilon; Ariel Felner; Roni Stern

Dynamic potential search on weighted graphs

Daniel Gilon
, Ariel Felner
, Roni Stern

Research output: Contribution to conference › Paper › peer-review

3 Scopus citations

Abstract

Dynamic Potential Search (DPS) is a recently introduced search algorithm that returns a bounded-suboptimal cost solution. DPS orders nodes in the open-list based on their potential which is a combination of both the g- and h-values of a node. In this paper we study the behavior of DPS on weighted graphs. In particular, we develop a new variant of DPS, called DPSU which calculates the potential by counting one for each edge regardless of its costs. We develop an eager version and a restrained version of DPSU. We then compare all these algorithms on a number of weighted graphs and study the pros and cons of each of them.

Original language	English
Pages	119-123
Number of pages	5
State	Published - 1 Jan 2017
Event	10th Annual Symposium on Combinatorial Search, SoCS 2017 - Pittsburgh, United States Duration: 16 Jun 2017 → 17 Jun 2017

Conference

Conference	10th Annual Symposium on Combinatorial Search, SoCS 2017
Country/Territory	United States
City	Pittsburgh
Period	16/06/17 → 17/06/17

ASJC Scopus subject areas

Computer Networks and Communications

Cite this

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title = "Dynamic potential search on weighted graphs",

abstract = "Dynamic Potential Search (DPS) is a recently introduced search algorithm that returns a bounded-suboptimal cost solution. DPS orders nodes in the open-list based on their potential which is a combination of both the g- and h-values of a node. In this paper we study the behavior of DPS on weighted graphs. In particular, we develop a new variant of DPS, called DPSU which calculates the potential by counting one for each edge regardless of its costs. We develop an eager version and a restrained version of DPSU. We then compare all these algorithms on a number of weighted graphs and study the pros and cons of each of them.",

author = "Daniel Gilon and Ariel Felner and Roni Stern",

note = "Publisher Copyright: Copyright c 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 10th Annual Symposium on Combinatorial Search, SoCS 2017 ; Conference date: 16-06-2017 Through 17-06-2017",

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pages = "119--123",

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T1 - Dynamic potential search on weighted graphs

AU - Gilon, Daniel

AU - Felner, Ariel

AU - Stern, Roni

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N2 - Dynamic Potential Search (DPS) is a recently introduced search algorithm that returns a bounded-suboptimal cost solution. DPS orders nodes in the open-list based on their potential which is a combination of both the g- and h-values of a node. In this paper we study the behavior of DPS on weighted graphs. In particular, we develop a new variant of DPS, called DPSU which calculates the potential by counting one for each edge regardless of its costs. We develop an eager version and a restrained version of DPSU. We then compare all these algorithms on a number of weighted graphs and study the pros and cons of each of them.

AB - Dynamic Potential Search (DPS) is a recently introduced search algorithm that returns a bounded-suboptimal cost solution. DPS orders nodes in the open-list based on their potential which is a combination of both the g- and h-values of a node. In this paper we study the behavior of DPS on weighted graphs. In particular, we develop a new variant of DPS, called DPSU which calculates the potential by counting one for each edge regardless of its costs. We develop an eager version and a restrained version of DPSU. We then compare all these algorithms on a number of weighted graphs and study the pros and cons of each of them.

UR - https://www.scopus.com/pages/publications/85050555244

M3 - Paper

AN - SCOPUS:85050555244

SP - 119

EP - 123

T2 - 10th Annual Symposium on Combinatorial Search, SoCS 2017

Y2 - 16 June 2017 through 17 June 2017

ER -

Dynamic potential search on weighted graphs

Abstract

Conference

ASJC Scopus subject areas

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