Name
Abstract | ||
|---|---|---|
The current investigations on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to automatically generate a good performing heuristic for the problem at hand. This can be done, for example, by automatically selecting and combining different low-level heuristics into a problem specific and effective strategy. Hyper-heuristics raise the level of generality on automated problem solving by attempting to select and/or generate tailored heuristics for the problem at hand. Some approaches like genetic programming have been proposed for this. In this paper, we explore an elegant nature-inspired alternative based on self-assembly construction processes, in which structures emerge out of local interactions between autonomous components. This idea arises from previous works in which computational models of self-assembly were subject to evolutionary design in order to perform the automatic construction of user-defined structures. Then, the aim of this paper is to present a novel methodology for the automated design of heuristics by means of self-assembly. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.4204/EPTCS.26.13 | ELECTRONIC PROCEEDINGS IN THEORETICAL COMPUTER SCIENCE |
Keywords | Field | DocType |
self assembly,evolutionary computing,artificial intelligent,computer model | Heuristic,Computer science,Genetic programming,Heuristics,Computational model,Artificial intelligence,Generality | Journal |
Volume | Issue | ISSN |
abs/1006.1 | 26 | 2075-2180 |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Germán Terrazas | 1 | 65 | 7.64 |
| Dario Landa Silva | 2 | 316 | 28.38 |
| Natalio Krasnogor | 3 | 1213 | 85.53 |