Evolutionary Learning Strategy using Bug-Based Search
Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence. Machine Learning. Pages 960-965.
Abstract
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization difficulties, especially in higher dimensions. To overcome such difficulties, we introduce a "bug-based" search strategy, and implement a system called BUGS2. The ideas behind this new approach are derived from biologically realistic bug behaviors. These ideas were confirmed empirically by applying them to some optimization and computer vision problems.
@inproceedings{ijcai1993p132,
title = {Evolutionary Learning Strategy using Bug-Based Search},
author = {Iba, Hitoshi and Higuchi, Tetsuya and de Garis, Hugo and Sato, Taisuke},
booktitle = {Proceedings of the Thirteenth International Joint Conference on
Artificial Intelligence, {IJCAI-93}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ruzena Bajcsy},
pages = {960--965},
year = {1993},
note = {Machine Learning},
url = {https://ijcai.org/proceedings/1993/132},
}
TY - CPAPER TI - Evolutionary Learning Strategy using Bug-Based Search AU - Iba, Hitoshi AU - Higuchi, Tetsuya AU - de Garis, Hugo AU - Sato, Taisuke T2 - Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, IJCAI-93 PB - International Joint Conferences on Artificial Intelligence PY - 1993 SP - 960 EP - 965 UR - https://ijcai.org/proceedings/1993/132 ER -Copied
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