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ANTSW
2008
Springer
15 years 7 months ago
Adaptive Particle Swarm Optimization
An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perfor...
Zhi-hui Zhan, Jun Zhang
CEC
2010
IEEE
15 years 6 months ago
A hormone-based controller for evolutionary multi-modular robotics: From single modules to gait learning
For any embodied, mobile, autonomous agent it is essential to control its actuators appropriately for the faced task. This holds for natural organisms as well as for robots. If sev...
Heiko Hamann, Jürgen Stradner, Thomas Schmick...
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
15 years 6 months ago
Multi-agent task allocation: learning when to say no
This paper presents a communication-less multi-agent task allocation procedure that allows agents to use past experience to make non-greedy decisions about task assignments. Exper...
Adam Campbell, Annie S. Wu, Randall Shumaker
149
Voted
TEC
2002
133views more  TEC 2002»
15 years 4 months ago
Learning and optimization using the clonal selection principle
The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that rec...
Leandro Nunes de Castro, Fernando J. Von Zuben
TKDE
2010
168views more  TKDE 2010»
15 years 3 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...