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Applying artificial intelligence algorithms in MOBA games

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Multiplayer Online Battle Arena games focus mainly on struggles between two teams of players. An increasing level of cyberbullying [1] discourages new players from the game and they often chose a different option, that is, a match against opponents controlled by the computer. The behavior of artificial foes can be dynamically fitted to user’s needs, in particular with regard to the difficulty of the game. In this paper we explore different approaches to provide an intelligent behavior of bots basing on more human-like combat predictions rather than instant, scripted behaviors.
Rocznik
Strony
53--64
Opis fizyczny
Bibliogr. 15 poz., rys., wykr.
Twórcy
  • Siedlce University of Natural Sciences and Humanities, Institute of Computer Science, ul. 3 Maja 54, 08-110 Siedlce, Poland
  • Siedlce University of Natural Sciences and Humanities, Institute of Computer Science, ul. 3 Maja 54, 08-110 Siedlce, Poland
Bibliografia
  • 1. Kwak Haewoon, Blackburn Jeremy, Han Seungyeop. Exploring Cyberbullying and Other Toxic Behavior in Team Competition Online Games, CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 3739-3748, 2015.
  • 2. Hamilton A. William, Garretson Oliver, Kerne Andruid, Streaming on Twitch: Fostering Participatory Communities of Play within Live Mixed Media, CHI '14 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1315-1324, 2014.
  • 3. Nae Vlad, Iosup Alexandru, Prodan Radu. Dynamic Resource Provisioning in Massively Multiplayer Online Games, IEEE Transactions on Parallel and Distributed Systems: 22(3), pp. 380–395, 2011.
  • 4. Kvanli Erik, Hammerstad Eirik M. A Coalition based Agent Design for Heroes of Newerth, Norwegian University of Science and Technology, Master’s Thesis, 2014.
  • 5. Lim, C. U., Baumgarten, R., Colton, S. Evolving behaviour trees for the commercial game DEFCON. In Applications of Evolutionary Computation, pp. 100-110, Springer, 2010.
  • 6. Victor do Nascimento Silva, Chaimowicz Luiz. A Tutor Agent for MOBA Games, Proceedings of the XIV Brazilian Symposium on Computer Games and Digital Entertainment (SBGames 2015), pp. 220-223, ISSN: 2179-2259, 2015.
  • 7. Victor do Nascimento Silva, Chaimowicz Luiz. On the Development of Intelligent Agents for MOBA Games, Proceedings of the XIV Brazilian Symposium on Computer Games and Digital Entertainment (SBGames 2015), pp. 131-139, ISSN: 2179-2259, 2015.
  • 8. Wiśniewski Mateusz. Zastosowanie Algorytmów Sztucznej Inteligencji w Grach typu MOBA (in Polish), Siedlce University of Natural Sciences and Humanities, Master’s Thesis, 2016.
  • 9. Siddhesh V. Kolwankar. Evolutionary Artificial Intelligence for MOBA / Action-RTS Games using Genetic Algorithms, International Journal of Computer Applications (IJCA) (0975 – 8887), pp. 29-31, 2012.
  • 10. Whitley Darrell. A genetic algorithm tutorial, Stat Comput. 4: 65, doi:10.1007/BF00175354, 1994.
  • 11. Creighton Henson Ryan. Unity 3d Game development by Example, ISBN 9781849690546, Packt Publishing, 2010.
  • 12. Brand Sandy. Efficient obstacle avoidance using autonomously generated navigation meshes, Delft University of Technology, Master’s Thesis, 2009.
  • 13. Kirkpatrick, S., Jr, C. G., Vecchi, M.: Optimization by simulated annealing, Sci., 220, pp. 671–680, 1983.
  • 14. Niewiadomski A., Skaruz J., Świtalski P., Penczek W. Concrete Planning in PlanICS Framework by Combining SMT with GEO and Simulated Annealing, Fundam. Inform. 147 (2016), pp. 289–313, IOS Press, DOI 10.3233/FI-2016-1409, 2016.
  • 15. Niewiadomski A., Skaruz J., Penczek W., Szreter M., Jarocki M. SMT Versus Genetic and OpenOpt Algorithms: Concrete Planning in the PlanICS Framework, Fundam. Inform. 135(4), pp. 451-466, 2014.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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