Optimizing Propositional Networks

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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 languageEnglish
Title of host publicationComputer Games. CGW 2016, GIGA 2016
PublisherSpringer
Pages133-151
DOIs
Publication statusPublished - 29 Apr 2017

Publication series

SeriesCommunications in Computer and Information Science
Volume705
ISSN1865-0929

Cite this

Sironi, C. F., & Winands, M. H. M. (2017). Optimizing Propositional Networks. In Computer Games. CGW 2016, GIGA 2016 (pp. 133-151). [Chapter 10] Springer. Communications in Computer and Information Science, Vol.. 705 https://doi.org/10.1007/978-3-319-57969-6_10