dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Broersen, J. | |
dc.contributor.author | Mens, K. van | |
dc.date.accessioned | 2012-06-21T17:01:12Z | |
dc.date.available | 2012-06-21 | |
dc.date.available | 2012-06-21T17:01:12Z | |
dc.date.issued | 2012 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/10551 | |
dc.description.abstract | Over the past decade, scientific artificial intelligence research has picked up real-time strategy video games as testbed for research. The large amount of data, the dynamic environment and strategic depth of the game makes the genre a challenge for scientific artificial intelligence research. This thesis is a comparative survey of two artificial intelligence techniques from scientific research, Case-based reasoning and Dynamic Scripting, to create a strong real-time strategy game playing agent. | |
dc.description.sponsorship | Utrecht University | |
dc.format.extent | 671456 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.title | Strategic reasoning in complex domains:
A comparative survey on scientific AI techniques to improve real-time strategy game AI. | |
dc.type.content | Bachelor Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | real-time strategy game, multi-agent, strategy, starcraft, AI, adaptive | |
dc.subject.courseuu | Kunstmatige Intelligentie | |