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020 _a9783031021220
024 7 _a10.1007/978-3-031-02122-0
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aGV1469.15
_b2020 EB
100 1 _aPérez Liébana, Diego
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9688284
245 1 0 _aGeneral Video Game Artificial Intelligence
_cby Diego Pérez Liébana, Simon M. Lucas, Raluca D. Gaina, Julian Togelius, Ahmed Khalifa, Jialin Liu
250 _a1st edition 2020
264 1 _aCham
_bSpringer International Publishing
_c2020
300 _a1 recurso en línea (XIV, 177 páginas)
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
490 0 _aSynthesis Lectures on Games and Computational Intelligence
_x2573-6493
505 0 _aPreface -- Acknowledgments -- Introduction -- VGDL and the GVGAI Framework -- Planning in GVGAI -- Frontiers of GVGAI Planning -- Learning in GVGAI -- Procedural Content Generation in GVGAI -- Automatic General Game Tuning -- GVGAI without VGDL -- GVGAI: What's Next? -- Bibliography -- Authors' Biographies.
520 _aResearch on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors during these years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.
988 _aSynthesis Collection of Technology_2020
650 7 _2embne
_9141365
_aVideojuegos
650 7 _2embne
_aInteligencia artificial
_9413115
700 1 _aLucas, Simon M.
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9688285
700 1 _aGaina, Raluca D.
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9688286
700 1 _aTogelius, Julian.
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_999600
700 1 _aKhalifa, Ahmed
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9688287
700 1 _aLiu, Jialin
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9688288
776 0 8 _iPrinted edition:
_z9783031001710
776 0 8 _iPrinted edition:
_z9783031009945
776 0 8 _iPrinted edition:
_z9783031032509
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02122-0
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b04/2023
_dz
_eIG
_zSI