Abstract
In this study, an innovative conception is conceived to break the development bottleneck of the traditional ECs at present. This innovative conception is bio-inspired evolutionary computing with context-awareness and collective-effect called as Next-Generation ECs (EC 2.0). For the property of context-awareness in EC 2.0, the individuals are able to observe environmental information by physic property. And, the individual can regularly and closely move to objective. In addition, the individual behaviors in collective-effect include competition, cooperation and conflict. The conflict behaviors of individuals such as difference, contradiction or inconsistence are considered to design the search strategy. The proposed guidable bat algorithm (GBA) is the paradigm of EC 2.0. The bats governed by GBA are able to rapidly and precisely discover the global optimal solution. The simulation results show that the solving efficiency and solution quality of GBA are better than BA’s, even well-known HBA’s.
| Original language | English |
|---|---|
| Pages (from-to) | 99-113 |
| Number of pages | 15 |
| Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Volume | 8916 |
| DOIs | |
| Publication status | Published - 2014 |
| Event | International Conference on Technologies and Applications of Artificial Intelligence - Taipei, Taiwan, Republic of China Duration: 21 Nov 2014 → 23 Nov 2014 Conference number: 19th |
Keywords
- Bio-inspired evolutionary computing
- Collective-effect
- Context-awareness
- Guidable bat algorithm (GBA)
- Next-generation evolutionary computing (EC 2.0)