Name
Abstract | ||
|---|---|---|
We perform laboratory experiments to elucidate the role of historical information in games involving human coordination. Our approach follows prior work studying human network coordination using the task of graph coloring. We first motivate this research by showing empirical evidence that the resolution of coloring conflicts is dependent upon the recent local history of that conflict. We also conduct two tailored experiments to manipulate the game history that can be used by humans in order to determine (i) whether humans use historical information, and (ii) whether they use it effectively. In the first variant, during the course of each coloring task, the network positions of the subjects were periodically swapped while maintaining the global coloring state of the network. In the second variant, participants completed a series of 2-coloring tasks, some of which were restarts from checkpoints of previous tasks. Thus, the participants restarted the coloring task from a point in the middle of a previous task without knowledge of the history that led to that point. We report on the game dynamics and average completion times for the diverse graph topologies used in the swap and restart experiments. |
Year | Venue | Field |
|---|---|---|
2012 | CoRR | Graph,Empirical evidence,Computer science,Game dynamics,Network topology,Artificial intelligence,Machine learning,Graph coloring |
DocType | Volume | Citations |
Journal | abs/1202.2503 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manuel Cebrián | 1 | 387 | 38.52 |
| Ramamohan Paturi | 2 | 1260 | 92.20 |
| Daniel Ricketts | 3 | 24 | 3.22 |