TY - GEN
T1 - Automated Design Competition Technical Report
T2 - 2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion
AU - Shu, Xiang
AU - Zhu, Yiyi
AU - Zhang, Renji
AU - Xia, Xiang
AU - Li, Bingdong
AU - Qian, Hong
N1 - Publisher Copyright:
© 2024 Copyright held by the owner/author(s).
PY - 2024/7/14
Y1 - 2024/7/14
N2 - The Automated Design Competition in GECCO'24 aims to find intelligent 3D agents that perform better in specific environments. To address this problem, this technical report proposes a Cascaded Structure and Parameter Optimization (CaSPO) framework. After constructing an initial population by using prior knowledge, CaSPO optimizes the mechanical structure, control system, and parameters sequentially to find good-performance agents. Experiments in different tasks and environments verify the effectiveness of the proposed CaSPO framework.
AB - The Automated Design Competition in GECCO'24 aims to find intelligent 3D agents that perform better in specific environments. To address this problem, this technical report proposes a Cascaded Structure and Parameter Optimization (CaSPO) framework. After constructing an initial population by using prior knowledge, CaSPO optimizes the mechanical structure, control system, and parameters sequentially to find good-performance agents. Experiments in different tasks and environments verify the effectiveness of the proposed CaSPO framework.
KW - cascaded optimization
KW - evolutionary algorithms
KW - framsticks
UR - https://www.scopus.com/pages/publications/85201934688
U2 - 10.1145/3638530.3664054
DO - 10.1145/3638530.3664054
M3 - 会议稿件
AN - SCOPUS:85201934688
T3 - GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion
SP - 3
EP - 4
BT - GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion
PB - Association for Computing Machinery, Inc
Y2 - 14 July 2024 through 18 July 2024
ER -