Abstract
Particle swarm optimization (PSO) is similar to genetic algorithm (GA) but employs different strategies and computational effort. Strategic defense military games require a high degree of coordination among the characters and thus are suitable to test the performance of algorithms. In this paper, we design a scenario of tower defense game and compare the performance of PSO and GA in terms of the damage value (fitness) and the convergence speed. The comparative analysis shows the similar optimum cannon placement is obtained using PSO and GA with similar effectiveness. In addition, the results of execution time (> 80 seconds) indicate that the single implement of PSO or GA is unsatisfied for real time strategy (RTS) games.
Original language | English |
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Title of host publication | 5th International Conference on Natural Computation, ICNC 2009 |
Pages | 387-392 |
Number of pages | 6 |
Volume | 5 |
DOIs | |
Publication status | Published - 1 Dec 2009 |
Event | 5th International Conference on Natural Computation, ICNC 2009 - Tianjian, China Duration: 14 Aug 2009 → 16 Aug 2009 |
Conference
Conference | 5th International Conference on Natural Computation, ICNC 2009 |
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Country | China |
City | Tianjian |
Period | 14/08/09 → 16/08/09 |
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Science Applications
- Software