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GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
15 years 10 months ago
A developmental model of neural computation using cartesian genetic programming
The brain has long been seen as a powerful analogy from which novel computational techniques could be devised. However, most artificial neural network approaches have ignored the...
Gul Muhammad Khan, Julian F. Miller, David M. Hall...
ECAL
2001
Springer
15 years 8 months ago
Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Rupp...
125
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ICANN
2005
Springer
15 years 9 months ago
Action Understanding and Imitation Learning in a Robot-Human Task
We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goaldirected imitation. The control architecture is b...
Wolfram Erlhagen, Albert Mukovskiy, Estela Bicho, ...
121
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IVC
2000
104views more  IVC 2000»
15 years 4 months ago
Learning spatio-temporal patterns for predicting object behaviour
Rule-based systems employed to model complex object behaviours, do not necessarily provide a realistic portrayal of true behaviour. To capture the real characteristics in a specif...
Neil Sumpter, Andrew J. Bulpitt
IDEAL
2004
Springer
15 years 9 months ago
In-Situ Learning in Multi-net Systems
Abstract. Multiple classifier systems based on neural networks can give improved generalisation performance as compared with single classifier systems. We examine collaboration in ...
Matthew C. Casey, Khurshid Ahmad