Name
Abstract | ||
|---|---|---|
In this paper, we improve on a previously proposed algorithm for exploring a 2-D environment with multiple robots using Potential Games. A potential game is a type of game that results in coordinated behaviours amongst players. This is done by enforcing strict rules for each player in selecting an action from its action set. As part of this game, we define a potential function for the game that is meaningful in terms of achieving the greater objective of exploring a space. Furthermore, an objective function is assigned for each player from this potential function. We then create an algorithm for the exploration of an obstaclefilled bounded space, and demonstrate through simulation how it outperforms an uncoordinated algorithm by reducing the time needed to uncover the space. This algorithm is then improved by having robots predict the future positions of all other robots. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SMC.2013.407 | SMC |
Keywords | Field | DocType |
uncoordinated algorithm,greater objective,potential games,2-d environment,action set,potential game,obstaclefilled bounded space,potential function,future position,objective function,cooperative exploration,game theory | Computer science,Potential game,Algorithmic game theory,Game theory,Artificial intelligence,Robot,Robotics,Machine learning,Bounded function | Conference |
ISSN | Citations | PageRank |
1062-922X | 0 | 0.34 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| George Philip | 1 | 1 | 0.71 |
| Howard M. Schwartz | 2 | 135 | 20.29 |
| Sidney Nascimento Givigi | 3 | 20 | 6.91 |