Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board Game
With the rapid advent of video games recently and the increasing numbers of players and gamers, only a tough game with high policy, actions, and tactics survives. How the game responds to opponent actions is the key issue of popular games. Many algorithms were proposed to solve this problem such as...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | International Journal of Computer Games Technology |
| Online Access: | http://dx.doi.org/10.1155/2016/7090757 |
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| author | Shahenda Sarhan Mohamed Abu ElSoud Hebatullah Rashed |
| author_facet | Shahenda Sarhan Mohamed Abu ElSoud Hebatullah Rashed |
| author_sort | Shahenda Sarhan |
| collection | DOAJ |
| description | With the rapid advent of video games recently and the increasing numbers of players and gamers, only a tough game with high policy, actions, and tactics survives. How the game responds to opponent actions is the key issue of popular games. Many algorithms were proposed to solve this problem such as Least-Squares Policy Iteration (LSPI) and State-Action-Reward-State-Action (SARSA) but they mainly depend on discrete actions, while agents in such a setting have to learn from the consequences of their continuous actions, in order to maximize the total reward over time. So in this paper we proposed a new algorithm based on LSPI called Least-Squares Continuous Action Policy Iteration (LSCAPI). The LSCAPI was implemented and tested on three different games: one board game, the 8 Queens, and two real-time strategy (RTS) games, StarCraft Brood War and Glest. The LSCAPI evaluation proved superiority over LSPI in time, policy learning ability, and effectiveness. |
| format | Article |
| id | doaj-art-39f1185d48ed464483529d4fe632feb7 |
| institution | Kabale University |
| issn | 1687-7047 1687-7055 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Computer Games Technology |
| spelling | doaj-art-39f1185d48ed464483529d4fe632feb72025-02-03T05:47:45ZengWileyInternational Journal of Computer Games Technology1687-70471687-70552016-01-01201610.1155/2016/70907577090757Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board GameShahenda Sarhan0Mohamed Abu ElSoud1Hebatullah Rashed2Computer Science Department, Faculty of Computers and Information, Mansoura University, Mansoura 35516, EgyptComputer Science Department, Faculty of Computers and Information, Mansoura University, Mansoura 35516, EgyptComputer Science Department, Faculty of Computers and Information, Mansoura University, Mansoura 35516, EgyptWith the rapid advent of video games recently and the increasing numbers of players and gamers, only a tough game with high policy, actions, and tactics survives. How the game responds to opponent actions is the key issue of popular games. Many algorithms were proposed to solve this problem such as Least-Squares Policy Iteration (LSPI) and State-Action-Reward-State-Action (SARSA) but they mainly depend on discrete actions, while agents in such a setting have to learn from the consequences of their continuous actions, in order to maximize the total reward over time. So in this paper we proposed a new algorithm based on LSPI called Least-Squares Continuous Action Policy Iteration (LSCAPI). The LSCAPI was implemented and tested on three different games: one board game, the 8 Queens, and two real-time strategy (RTS) games, StarCraft Brood War and Glest. The LSCAPI evaluation proved superiority over LSPI in time, policy learning ability, and effectiveness.http://dx.doi.org/10.1155/2016/7090757 |
| spellingShingle | Shahenda Sarhan Mohamed Abu ElSoud Hebatullah Rashed Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board Game International Journal of Computer Games Technology |
| title | Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board Game |
| title_full | Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board Game |
| title_fullStr | Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board Game |
| title_full_unstemmed | Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board Game |
| title_short | Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board Game |
| title_sort | enhancing video games policy based on least squares continuous action policy iteration case study on starcraft brood war and glest rts games and the 8 queens board game |
| url | http://dx.doi.org/10.1155/2016/7090757 |
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