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GECCO
2007
Springer
131views Optimization» more  GECCO 2007»
16 years 17 days ago
Using feedback to regulate gene expression in a developmental control architecture
We present what we believe is the first attempt to physically reconstruct the exploratory mechanism of genetic regulatory networks. Feedback plays a crucial role during developme...
Kester Clegg, Susan Stepney, Tim Clarke
GPEM
2002
95views more  GPEM 2002»
15 years 6 months ago
On Appropriate Adaptation Levels for the Learning of Gene Linkage
A number of algorithms have been proposed aimed at tackling the problem of learning "Gene Linkage" within the context of genetic optimisation, that is to say, the problem...
James Smith
ATAL
2008
Springer
15 years 8 months ago
Efficient multi-agent reinforcement learning through automated supervision
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
IJRR
2008
139views more  IJRR 2008»
15 years 6 months ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal
GECCO
2006
Springer
145views Optimization» more  GECCO 2006»
15 years 10 months ago
Multi-objective genetic algorithms for pipe arrangement design
This paper presents an automatic design method for piping arrangement. A pipe arrangement design problem is proposed for a space in which many pipes and objects co-exist. This pro...
Satoshi Ikehira, Hajime Kimura