Name
Abstract | ||
|---|---|---|
We employ an agent-based model to show that memory and the absence of an a priori best strategy are sufficient for self-segregation and clustering to emerge in a complex adaptive system with discrete agents that do not compete over a limited resource nor contend in a winner-take-all scenario. An agent starts from a corner of a two-dimensional lattice and aims to reach a randomly selected site in the opposite side within the shortest possible time. The agent is isolated during the course of its journey and does not interact with other agents. Time-bound obstacles appear at random lattice locations and the agent must decide whether to challenge or evade any obstacle blocking its path. The agent is capable of adapting a strategy in dealing with an obstacle. We analyze the dependence of strategy-retention time with strategy for both memory-based and memory-less agents. We derive the equality spectrum to establish the environmental conditions that favor the existence of an a priori best strategy. We found that memory-less agents do not polarize into two opposite strategy-retention time distributions nor cluster toward a center distribution. (c) 2004 Wiley Periodicals, Inc. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1002/cplx.20008 | COMPLEXITY |
Keywords | Field | DocType |
self-segregation, clustering, strategy, retention time, equality spectrum, memory-less agents | Obstacle,Lattice (order),A priori and a posteriori,Artificial intelligence,Cluster analysis,Complex adaptive system,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
9 | 3 | 1076-2787 |
Citations | PageRank | References |
2 | 0.43 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marcelino Quito Jr. | 1 | 2 | 0.43 |
| C. Monterola | 2 | 5 | 3.43 |
| Caesar A. Saloma | 3 | 21 | 2.66 |