Name
Abstract | ||
|---|---|---|
We do not attempt to provide yet another definition of self-organization, but explore the conditions under which we can model a system as self-organizing. These involve the dynamics of entropy, and the purpose, aspects, and description level chosen by an observer. We show how, changing the level or "graining" of description, the same system can appear self-organizing or self-disorganizing. We discuss ontological issues we face when studying self-organizing systems, and analyse when designing and controlling artificial self-organizing systems is useful. We conclude that self-organization is a way of observing systems, not an absolute class of systems. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-39432-7_65 | ADVANCES IN ARTIFICIAL LIFE, PROCEEDINGS |
Keywords | DocType | Volume |
neural network,self organization,statistical mechanics,computational complexity | Conference | 2801 |
ISSN | Citations | PageRank |
0302-9743 | 55 | 3.06 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carlos Gershenson | 1 | 392 | 42.34 |
| Francis Heylighen | 2 | 217 | 20.62 |