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» Learning for Evolutionary Design
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126
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ATAL
2003
Springer
15 years 7 months ago
A selection-mutation model for q-learning in multi-agent systems
Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...
Karl Tuyls, Katja Verbeeck, Tom Lenaerts
147
Voted
CEC
2009
IEEE
15 years 9 months ago
Evolving modular neural-networks through exaptation
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...
Jean-Baptiste Mouret, Stéphane Doncieux
ARCS
2006
Springer
15 years 6 months ago
Biologically-Inspired Optimization of Circuit Performance and Leakage: A Comparative Study
State-of-the-art technologies in very large scale integration (VLSI) allow for the realization of gates with varying energy consumptions and hence delays (i.e., processing speeds) ...
Ralf Salomon, Frank Sill
160
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GECCO
2009
Springer
113views Optimization» more  GECCO 2009»
15 years 12 days ago
Single step evolution of robot controllers for sequential tasks
The generation of robot controllers for a task requiring a sequence of elementary behaviors is still a challenge. If these behaviors are known, intermediate steps can be given to ...
Stéphane Doncieux, Jean-Baptiste Mouret
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
15 years 9 months ago
An evolutionary approach to constructive induction for link discovery
This paper presents a genetic programming-based symbolic regression approach to the construction of relational features in link analysis applications. Specifically, we consider t...
Tim Weninger, William H. Hsu, Jing Xia, Waleed Alj...