Optimizing Propositional Networks

Chiara F. Sironi; Mark H. M. Winands

doi:10.1007/978-3-319-57969-6_10

Optimizing Propositional Networks

^*Corresponding author for this work

Networks and Strategic Optimization

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

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Abstract

General game playing (ggp) programs need a game description language (gdl) reasoner to be able to interpret the game rules and search for the best actions to play in the game. One method for interpreting the game rules consists of translating the gdl game description into an alternative representation that the player can use to reason more efficiently on the game. The propositional network (propnet) is an example of such method. The use of propnets in ggp has become popular due to the fact that propnets can speed up the reasoning process by several orders of magnitude compared to custom-made or prolog-based gdl reasoners, improving the quality of the search for the best actions. This paper analyzes the performance of a propnet-based reasoner and evaluates four different optimizations for the propnet structure that can help further increase its reasoning speed in terms of visited game states per second.

Original language	English
Title of host publication	Computer Games. CGW 2016, GIGA 2016
Publisher	Springer
Pages	133-151
DOIs	https://doi.org/10.1007/978-3-319-57969-6_10
Publication status	Published - 29 Apr 2017

Publication series

Series	Communications in Computer and Information Science
Volume	705
ISSN	1865-0929

Access to Document

10.1007/978-3-319-57969-6_10

Full text Final published version, 287 KBLicence: Taverne

http://link.springer.com/10.1007/978-3-319-57969-6_10

Cite this

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title = "Optimizing Propositional Networks",

abstract = "General game playing (ggp) programs need a game description language (gdl) reasoner to be able to interpret the game rules and search for the best actions to play in the game. One method for interpreting the game rules consists of translating the gdl game description into an alternative representation that the player can use to reason more efficiently on the game. The propositional network (propnet) is an example of such method. The use of propnets in ggp has become popular due to the fact that propnets can speed up the reasoning process by several orders of magnitude compared to custom-made or prolog-based gdl reasoners, improving the quality of the search for the best actions. This paper analyzes the performance of a propnet-based reasoner and evaluates four different optimizations for the propnet structure that can help further increase its reasoning speed in terms of visited game states per second.",

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AB - General game playing (ggp) programs need a game description language (gdl) reasoner to be able to interpret the game rules and search for the best actions to play in the game. One method for interpreting the game rules consists of translating the gdl game description into an alternative representation that the player can use to reason more efficiently on the game. The propositional network (propnet) is an example of such method. The use of propnets in ggp has become popular due to the fact that propnets can speed up the reasoning process by several orders of magnitude compared to custom-made or prolog-based gdl reasoners, improving the quality of the search for the best actions. This paper analyzes the performance of a propnet-based reasoner and evaluates four different optimizations for the propnet structure that can help further increase its reasoning speed in terms of visited game states per second.

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