dc.contributor.author | Cook, M | en_US |
dc.contributor.author | Raad, A | en_US |
dc.contributor.author | 2019 IEEE Conference on Games (CoG) | en_US |
dc.date.accessioned | 2019-11-28T11:50:28Z | |
dc.date.issued | 2019-09-26 | en_US |
dc.identifier.isbn | 9781728118840 | en_US |
dc.identifier.issn | 2325-4270 | en_US |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/61609 | |
dc.description.abstract | Automatically analysing games is an important challenge for automated game design, general game playing, and co-creative game design tools. However, understanding the nature of an unseen game is extremely difficult due to the lack of a priori design knowledge and heuristics. In this paper we formally define hyperstate space graphs, a compressed form of state space graphs which can be constructed without any prior design knowledge about a game. We show how hyperstate space graphs produce compact representations of games which closely relate to the heuristics designed by hand for search-based AI agents; we show how hyperstate space graphs also relate to modern ideas about game design; and we point towards future applications for hyperstates across game AI research. | en_US |
dc.title | Hyperstate space graphs for automated game analysis | en_US |
dc.type | Conference Proceeding | |
dc.rights.holder | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
dc.identifier.doi | 10.1109/CIG.2019.8848026 | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Published | en_US |
pubs.volume | 2019-August | en_US |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |