Name
Abstract | ||
|---|---|---|
This paper presents a competitive combat strategy and tactics in RTS Games AI. To put it simply, if a player is building up base, he is losing out on creating an army and If he is building up his army, he is losing out on having a strong base. The key to winning, in StarCraft or any other RTS game is to balance strategy, tactics, macro and micro. To improve the game, one has to be able to keep track of everything that's going on over the entire map. And one must be able to give orders quickly and efficiently so in this paper we propose a competitive battle strategy with the help of a plot and decision tree. We simulate the strategy in MicroRTS developed in java EE by conducting a game-play between human player and MicroRTS AI (Game AI), though our proposed strategy out-performs the Game AI rarely as we did not account game playing-speed that makes a huge difference in victory but at least we succeeded in introducing a strategy that could well compete the Game AI and may defeat it but rarely. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-77383-4_1 | ADVANCES IN MULTIMEDIA INFORMATION PROCESSING - PCM 2017, PT II |
Keywords | Field | DocType |
Combat strategy,Game AI,MicroRTS,Macro management,Real time strategy games,StarCraft | Computer vision,Decision tree,Computer security,Computer science,Victory,Artificial intelligence,Macro,Battle | Conference |
Volume | ISSN | Citations |
10736 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 9 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adil Khan | 1 | 22 | 11.68 |
| kai yang | 2 | 11 | 6.35 |
| Yunsheng Fu | 3 | 27 | 2.99 |
| Fang Lou | 4 | 17 | 3.07 |
| Worku Jifara | 5 | 0 | 0.34 |
| Feng Jiang | 6 | 75 | 12.29 |
| Liu Shaohui | 7 | 0 | 1.01 |