dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Rin, Benjamin | |
dc.contributor.author | Donkers, Mitchell | |
dc.date.accessioned | 2024-09-12T23:02:06Z | |
dc.date.available | 2024-09-12T23:02:06Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/47735 | |
dc.description.abstract | In this thesis we look at some of the proofs of proven EXPTIME-complete games and give our own EXPTIME-completeness proof. We specifically look at chess and American checkers, for which we will describe their EXPTIME-hardness proofs. Furthermore for American checkers we will explain why the current proof is insufficient to prove any other checker variant and show an attempt at adapting it for international checkers. Next we give our own proof for perfect information Stratego being EXPTIME-complete. We do this by first proving a new game, that we call G2.5, to be EXPTIME-complete and making a reduction from that to stratego. The EXPTIME-hardness result within the EXPTIME-completeness proof can also be seen to apply to Stratego without perfect information. Lastly we will give some insights on how to improve both the checkers proof and our stratego proof. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | This thesis looks at some EXPTIME-completeness proofs for board games. We also show that athough it is claimed that checkers is EXPTIME-complete that this only holds for American checkers. Any other checker variant is not yet proven to be EXPTIME-complete.
Further more we prove that a new game (G2.5) and use that for our Stratego proof.
We proof that Stratego with perfect information is EXPTIME-complete and Stratego without perfect information is EXPTIME-hard. | |
dc.title | The computational complexity of Stratego perfect strategy | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | EXPTIME-completeness; EXPTIME-hardness; computational complexity; board games | |
dc.subject.courseuu | Artificial Intelligence | |
dc.thesis.id | 39289 | |